scholarly journals Regional Decadal Climate Predictions Using an Ensemble of WRF Parameterizations Driven by the MIROC5 GCM

2019 ◽  
Vol 58 (3) ◽  
pp. 527-549 ◽  
Author(s):  
Ehud Strobach ◽  
Golan Bel
Keyword(s):  
Surface Layer ◽  
Surface Temperature ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Wrf Model ◽  
Maximum Surface ◽  
Surface Temperatures

AbstractRegional climate models (RCMs) are expected to provide better representations of the climate dynamics because of their higher spatial resolutions. Here, we generated an ensemble of decadal (2006–36) RCM predictions for the area of Israel, which spans a considerable climatic gradient and comprises complex terrain. We used the WRF Model forced by the MIROC5 global climate model (GCM). The ensemble was generated by choosing different combinations of radiation, microphysics, surface layer, and planetary boundary layer parameterizations. The simulation results were compared with meteorological station data for the first simulated decade. For the minimum surface temperature, all the RCM configurations performed better than the driving GCM, while for the maximum surface temperature, only three out of eight configurations improved the predictions. The RCM configurations had higher errors in predicting the precipitation, but four configurations had comparable errors to the GCM. For the next two decades, the ensemble average predicts an increase of 0.51° and 0.40°C decade−1 for the average daily minimum and maximum surface temperatures, respectively. No significant change is predicted in the precipitation. We found that all the parameterizations affect the predictions of the surface temperatures and precipitation [e.g., the CAM radiation scheme simulates colder temperatures than the RRTM for GCMs (RRTMG)] but the PBL and surface layer scheme has the largest effect on the errors. Spectral nudging was found to have a considerable effect on the deviations of the precipitation predicted by the WRF configurations from the predictions of the GCM and a much smaller effect on the surface temperature predictions.

scholarly journals Quantification of the Expected Changes in Annual Maximum Daily Precipitation Quantiles under Climate Change in the Iberian Peninsula

Proceedings ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 23 ◽  
Author(s):  
Carlos Garijo ◽  
Luis Mediero
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Control Period ◽  
Regional Climate Models ◽  
The Future

Climate model projections can be used to assess the expected behaviour of extreme precipitations in the future due to climate change. The European part of the Coordinated Regional Climate Downscalling Experiment (EURO-CORDEX) provides precipitation projections for the future under various representative concentration pathways (RCPs) through regionalised Global Climate Model (GCM) outputs by a set of Regional Climate Models (RCMs). In this work, 12 combinations of GCM and RCM under two scenarios (RCP 4.5 and RCP 8.5) supplied by the EURO-CORDEX are analysed for the Iberian Peninsula. Precipitation quantiles for a set of probabilities of non-exceedance are estimated by using the Generalized Extreme Value (GEV) distribution and L-moments. Precipitation quantiles expected in the future are compared with the precipitation quantiles in the control period for each climate model. An approach based on Monte Carlo simulations is developed in order to assess the uncertainty from the climate model projections. Expected changes in the future are compared with the sampling uncertainty in the control period. Thus, statistically significant changes are identified. The higher the significance threshold, the fewer cells with significant changes are identified. Consequently, a set of maps are obtained in order to assist the decision-making process in subsequent climate change studies.

Quantification of terrestrial regional climate variability from a large database of pollen-based reconstructions and implications for future projections

2020 ◽  
Author(s):  
Raphael Hébert ◽  
Ulrike herzschuh ◽  
Thomas Laepple
Keyword(s):  
Climate Variability ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Irregular Sampling ◽  
Large Database ◽  
Spatial Correlation Structure ◽  
Pollen Records

<p>Multidecadal to millenial timescale climate variability has been investigated over the ocean</p><p>using extensive proxy data and it was found to yield coherent interproxy estimates of global and regional sea-surface temperature (SST) climate variability (Laepple and Huybers, 2014). Global Climate Model (GCM) simulations on the other hand, were found to exhibit an increasingly large deficit of regional SST climate variability for increasingly longer timescales.</p><p>Further investigation is needed to better quantify terrestrial climate variability for long</p><p>timescales and validate climate models.</p><p>Vegetation related proxies such as tree rings and pollen records are the most widespread</p><p>types of archives available to investigate terrestrial climate variability. Tree ring records are</p><p>particularly useful for short time scales estimates due to their annual resolution, while pollen-based reconstructions are necessary to cover the longer timescales. In the present work, we use a large database of 1873 pollen records covering the northern hemisphere in order to quantify Holocene vegetation and climate variability for the first time at centennial to multi-millenial timescales.</p><p>To ensure the robustness of our results, we are particularly interested in the spatio-temporal representativity of the archived signal in pollen records after taking into account the effective spatial scale, the intermittent and irregular sampling, the age-uncertainty and the sediment mixing effect. A careful treatment of the proxy formation allows us to investigate the spatial correlation structure of the pollen-based climate reconstructions as a function of timescales. The pollen data results are then contrasted with the analysis replicated using transient Holocene simulations produced with state-of-the-art climate models as well as stochastic climate model simulations.Our results indicate a substantial gap in terrestrial climate variability between the climate model simulations and the pollen reconstructions at centennial to multi-millenial timescales, mirroring the variability gap found in the marine domain. Finally, we investigate how future climate model projections with greater internal variability would be affected, and how this increases the uncertainty of regional land temperature projections.</p>

scholarly journals Technical challenges and solutions in representing lakes when using WRF in downscaling applications

2014 ◽  
Vol 7 (5) ◽  
pp. 7121-7150 ◽  
Author(s):  
M. S. Mallard ◽  
C. G. Nolte ◽  
T. L. Spero ◽  
O. R. Bullock ◽  
K. Alapaty ◽  
...  
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Wrf Model ◽  
Ice Cover ◽  
Alternative Methods ◽  
Weather Research And Forecasting ◽  
Inland Lakes ◽  
Air Temperatures

Abstract. The Weather Research and Forecasting (WRF) model is commonly used to make high resolution future projections of regional climate by downscaling global climate model (GCM) outputs. Because the GCM fields are typically at a much coarser spatial resolution than the target regional downscaled fields, inland lakes are often poorly resolved in the driving global fields, if they are resolved at all. In such an application, using WRF's default interpolation methods can result in unrealistic lake temperatures and ice cover at inland water points. Prior studies have shown that lake temperatures and ice cover impact the simulation of other surface variables, such as air temperatures and precipitation, two fields that are often used in regional climate applications to understand the impacts of climate change on human health and the environment. Here, alternative methods for setting lake surface variables in WRF for downscaling simulations are presented and contrasted.

scholarly journals Technical challenges and solutions in representing lakes when using WRF in downscaling applications

2015 ◽  
Vol 8 (4) ◽  
pp. 1085-1096 ◽  
Author(s):  
M. S. Mallard ◽  
C. G. Nolte ◽  
T. L. Spero ◽  
O. R. Bullock ◽  
K. Alapaty ◽  
...  
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Wrf Model ◽  
Ice Cover ◽  
Alternative Methods ◽  
Weather Research And Forecasting ◽  
Air Temperatures ◽  
Impacts Of Climate Change

Abstract. The Weather Research and Forecasting (WRF) model is commonly used to make high-resolution future projections of regional climate by downscaling global climate model (GCM) outputs. Because the GCM fields are typically at a much coarser spatial resolution than the target regional downscaled fields, lakes are often poorly resolved in the driving global fields, if they are resolved at all. In such an application, using WRF's default interpolation methods can result in unrealistic lake temperatures and ice cover at inland water points. Prior studies have shown that lake temperatures and ice cover impact the simulation of other surface variables, such as air temperatures and precipitation, two fields that are often used in regional climate applications to understand the impacts of climate change on human health and the environment. Here, alternative methods for setting lake surface variables in WRF for downscaling simulations are presented and contrasted.

scholarly journals Regional, Very Heavy Daily Precipitation in NARCCAP Simulations

2013 ◽  
Vol 14 (4) ◽  
pp. 1212-1227 ◽  
Author(s):  
Sho Kawazoe ◽  
William J. Gutowski
Keyword(s):  
Mississippi River ◽  
Climate Models ◽  
Climate Model ◽  
Daily Precipitation ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Heavy Precipitation ◽  
River Region ◽  
Precipitation Events

Abstract The authors analyze the ability of the North American Regional Climate Change Assessment Program's ensemble of climate models to simulate very heavy daily precipitation and its supporting processes, comparing simulations that used observation-based boundary conditions with observations. The analysis includes regional climate models and a time-slice global climate model that all used approximately half-degree resolution. Analysis focuses on an upper Mississippi River region for winter (December–February), when it is assumed that resolved synoptic circulation governs precipitation. All models generally reproduce the precipitation-versus-intensity spectrum seen in observations well, with a small tendency toward producing overly strong precipitation at high-intensity thresholds, such as the 95th, 99th, and 99.5th percentiles. Further analysis focuses on precipitation events exceeding the 99.5th percentile that occur simultaneously at several points in the region, yielding so-called “widespread events.” Examination of additional fields shows that the models produce very heavy precipitation events for the same physical conditions seen in the observations.

scholarly journals The CORDEX-CORE EXP-I initiative: Description and highlight results from the initial analysis

2021 ◽  
pp. 1-52
Author(s):  
Filippo Giorgi ◽  
Erika Coppola ◽  
Daniela Jacob ◽  
Claas Teichmann ◽  
Sabina Abba Omar ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Regional Climate Models ◽  
Added Value ◽  
Initial Analysis ◽  
Wide Range

AbstractWe describe the first effort within the Coordinated Regional Climate Downscaling Experiment - Coordinated Output for Regional Evaluation, or CORDEX-CORE EXP-I. It consists of a set of 21st century projections with two regional climate models (RCMs) downscaling three global climate model (GCM) simulations from the CMIP5 program, for two greenhouse gas concentration pathways (RCP8.5 and RCP2.6), over 9 CORDEX domains at ~25 km grid spacing. Illustrative examples from the initial analysis of this ensemble are presented, covering a wide range of topics, such as added value of RCM nesting, extreme indices, tropical and extratropical storms, monsoons, ENSO, severe storm environments, emergence of change signals, energy production. They show that the CORDEX-CORE EXP-I ensemble can provide downscaled information of unprecedented comprehensiveness to increase understanding of processes relevant for regional climate change and impacts, and to assess the added value of RCMs. The CORDEX-CORE EXP-I dataset, which will be incrementally augmented with new simulations, is intended to be a public resource available to the scientific and end-user communities for application to process studies, impacts on different socioeconomic sectors and climate service activities. The future of the CORDEX-CORE initiative is also discussed.

Towards Assessing NARCCAP Regional Climate Model Credibility for the North American Monsoon: Current Climate Simulations*

2013 ◽  
Vol 26 (22) ◽  
pp. 8802-8826 ◽  
Author(s):  
Melissa S. Bukovsky ◽  
David J. Gochis ◽  
Linda O. Mearns
Keyword(s):  
North American ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
North American Monsoon ◽  
The North ◽  
Current Climate ◽  
Depth Analysis

Abstract The authors examine 17 dynamically downscaled simulations produced as part of the North American Regional Climate Change Assessment Program (NARCCAP) for their skill in reproducing the North American monsoon system. The focus is on precipitation and the drivers behind the precipitation biases seen in the simulations of the current climate. Thus, a process-based approach to the question of model fidelity is taken in order to help assess confidence in this suite of simulations. The results show that the regional climate models (RCMs) forced with a reanalysis product and atmosphere-only global climate model (AGCM) time-slice simulations perform reasonably well over the core Mexican and southwest United States regions. Some of the dynamically downscaled simulations do, however, have strong dry biases in Arizona that are related to their inability to develop credible monsoon flow structure over the Gulf of California. When forced with different atmosphere–ocean coupled global climate models (AOGCMs) for the current period, the skill of the RCMs subdivides largely by the skill of the forcing or “parent” AOGCM. How the inherited biases affect the RCM simulations is investigated. While it is clear that the AOGCMs have a large influence on the RCMs, the authors also demonstrate where the regional models add value to the simulations and discuss the differential credibility of the six RCMs (17 total simulations), two AGCM time slices, and four AOGCMs examined herein. It is found that in-depth analysis of parent GCM and RCM scenarios can identify a meaningful subset of models that can produce credible simulations of the North American monsoon precipitation.

scholarly journals Downscaling the climate change for oceans around Australia

2012 ◽  
Vol 5 (1) ◽  
pp. 425-458 ◽  
Author(s):  
M. A. Chamberlain ◽  
C. Sun ◽  
R. J. Matear ◽  
M. Feng ◽  
S. J. Phipps
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Ocean Model ◽  
Global Climate Models ◽  
Global Ocean ◽  
Coupled Models

Abstract. At present, global climate models used to project changes in climate do not resolve mesoscale ocean features such as boundary currents and eddies. These missing features may be important to realistically project the marine impacts of climate change. Here we present a framework for dynamically downscaling coarse climate change projections utilising a global ocean model that resolves these features in the Australian region. The downscaling model used here is ocean-only. The ocean feedback on the air-sea fluxes is explored by restoring to surface temperature and salinity, as well as a calculated feedback to wind stress. These feedback approximations do not replace the need for fully coupled models, but they allow us to assess the sensitivity of the ocean in downscaled climate change simulations. Significant differences are found in sea surface temperature, salinity, stratification and transport between the downscaled projections and those of the climate model. While the magnitude of the climate change differences may vary with the feedback parameterisation used, the patterns of the climate change differences are consistent and develop rapidly indicating they are mostly independent of feedback that ocean differences may have on the air-sea fluxes. Until such a time when it is feasible to regularly run a global climate model with eddy resolution, our framework for ocean climate change downscaling provides an attractive way to explore how climate change may affect the mesoscale ocean environment.

scholarly journals Assessing Past Climate Biases and the Added Value of CORDEX-CORE Precipitation Simulations over Africa

2021 ◽  
Vol 13 (11) ◽  
pp. 2058
Author(s):  
Gnim Tchalim Gnitou ◽  
Guirong Tan ◽  
Ruoyun Niu ◽  
Isaac Kwesi Nooni
Keyword(s):  
High Resolution ◽  
Climate Models ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Added Value ◽  
Spatial Coverage ◽  
Wide Range

The present study investigates the skills of CORDEX-CORE precipitation outputs in simulating Africa’s key seasonal climate features, emphasizing the added value (AV) of the dynamical downscaling approach from which they were derived. The results indicate the models’ good skills in capturing African rainfall patterns and dynamics at satellite-based observation resolutions, with up to 65.17% significant positive AV spatial coverage for the CCLM5 model and up to 55.47% significant positive AV spatial coverage for the REMO model. Unavoidable biases are however present in rainfall-abundant areas and are reflected in the AV results, but vary based on the season, the sub-area, and the Global Climate Model–Regional Climate Models (GCM-RCM) combination considered. The RCMs’ ensemble mean generally performs better than individual GCM–RCM simulations. A further analysis of the GCM–RCM model chain indicates a strong influence of the dynamical downscaling approach on the driving GCMs. However, exceptions are found in some seasons for specific RCMs’ outputs, where GCMs are influential. The findings also revealed that observational uncertainties can influence AV and contribute to a 6 to 34% difference in significant positive AV spatial coverage results. An analysis of these results suggests that the AV by CORDEX-CORE simulations over Africa depend on how well the GCM physics are integrated to those of the RCMs and how these features are accommodated in the high-resolution setting of the downscaling experiments. The deficiencies of the CORDEX-CORE simulations could be related to how well key processes are represented within the RCM models. For Africa, these results show that CORDEX-CORE products could be adequate for a wide range of high-resolution precipitation data applications.

scholarly journals Improved Representation of Surface Spectral Emissivity in a Global Climate Model and Its Impact on Simulated Climate

2018 ◽  
Vol 31 (9) ◽  
pp. 3711-3727 ◽  
Author(s):  
Xianglei Huang ◽  
Xiuhong Chen ◽  
Mark Flanner ◽  
Ping Yang ◽  
Daniel Feldman ◽  
...  
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Spectral Emissivity ◽  
Polar Regions ◽  
Simulated Climate ◽  
Longwave Flux

Surface longwave emissivity can be less than unity and vary significantly with frequency. However, most climate models still assume a blackbody surface in the longwave (LW) radiation scheme of their atmosphere models. This study incorporates realistic surface spectral emissivity into the atmospheric component of the Community Earth System Model (CESM), version 1.1.1, and evaluates its impact on simulated climate. By ensuring consistency of the broadband surface longwave flux across different components of the CESM, the top-of-the-atmosphere (TOA) energy balance in the modified model can be attained without retuning the model. Inclusion of surface spectral emissivity, however, leads to a decrease of net upward longwave flux at the surface and a comparable increase of latent heat flux. Global-mean surface temperature difference between the modified and standard CESM simulation is 0.20 K for the fully coupled run and 0.45 K for the slab-ocean run. Noticeable surface temperature differences between the modified and standard CESM simulations are seen over the Sahara Desert and polar regions. Accordingly, the climatological mean sea ice fraction in the modified CESM simulation can be less than that in the standard CESM simulation by as much as 0.1 in some regions. When spectral emissivities of sea ice and open ocean surfaces are considered, the broadband LW sea ice emissivity feedback is estimated to be −0.003 W m−2 K−1, assuming flat ice emissivity as sea ice emissivity, and 0.002 W m−2 K−1, assuming coarse snow emissivity as sea ice emissivity, which are two orders of magnitude smaller than the surface albedo feedback.

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