scholarly journals Use of very high resolution climate model data for hydrological modelling: estimation of potential evaporation

2015 ◽  
Vol 47 (3) ◽  
pp. 660-670 ◽  
Author(s):  
Alison C. Rudd ◽  
Alison L. Kay
Keyword(s):  
High Resolution ◽  
Boundary Conditions ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Hydrological Models ◽  
Potential Evaporation ◽  
Model Data ◽  
Very High

Climate model data are increasingly used to drive hydrological models, to assess the possible impacts of climate change on river flows. Hydrological models often require potential evaporation (PE) from vegetation, alongside precipitation, but PE is not usually output by climate models so has to be estimated from other meteorological variables. Here, the Penman–Monteith formula is applied to estimate PE using data from a 12 km Regional Climate Model (RCM) and a nested very high resolution (1.5 km) RCM covering southern Britain. PE estimates from RCM runs driven by reanalysis boundary conditions are compared to observation-based PE data, to assess performance. The comparison shows that both the 1.5 and 12 km RCMs reproduce observation-based PE well, on daily and monthly time-steps, and enables choices to be made about application of the formula using the available data. Data from Current and Future RCM runs driven by boundary conditions from a Global Climate Model are then used to investigate potential future changes in PE, and how certain factors affect those changes. In particular, the importance of including changes in canopy resistance is demonstrated. PE projections are also shown to vary to some extent according to how aerosols are modelled in the RCMs.

scholarly journals Response of extreme precipitation to uniform surface warming in quasi-global aquaplanet simulations at high resolution

2021 ◽  
Vol 379 (2195) ◽  
pp. 20190543
Author(s):  
P. A. O’Gorman ◽  
Z. Li ◽  
W. R. Boos ◽  
J. Yuval
Keyword(s):  
High Resolution ◽  
Climate Models ◽  
Climate Model ◽  
Flash Flood ◽  
Global Climate ◽  
Global Climate Model ◽  
Global Climate Models ◽  
Precipitation Extremes ◽  
Coarse Grained ◽  
The Tropics

Projections of precipitation extremes in simulations with global climate models are very uncertain in the tropics, in part because of the use of parameterizations of deep convection and model deficiencies in simulating convective organization. Here, we analyse precipitation extremes in high-resolution simulations that are run without a convective parameterization on a quasi-global aquaplanet. The frequency distributions of precipitation rates and precipitation cluster sizes in the tropics of a control simulation are similar to the observed distributions. In response to climate warming, 3 h precipitation extremes increase at rates of up to 9 %   K − 1 in the tropics because of a combination of positive thermodynamic and dynamic contributions. The dynamic contribution at different latitudes is connected to the vertical structure of warming using a moist static stability. When the precipitation rates are first averaged to a daily timescale and coarse-grained to a typical global climate-model resolution prior to calculating the precipitation extremes, the response of the precipitation extremes to warming becomes more similar to what was found previously in coarse-resolution aquaplanet studies. However, the simulations studied here do not exhibit the high rates of increase of tropical precipitation extremes found in projections with some global climate models. This article is part of a discussion meeting issue ‘Intensification of short-duration rainfall extremes and implications for flash flood risks’.

scholarly journals Evaluation of extreme sub-daily precipitation in high-resolution global climate model simulations

2021 ◽  
Vol 379 (2195) ◽  
pp. 20190545 ◽  
Author(s):  
Michael Wehner ◽  
Jiwoo Lee ◽  
Mark Risser ◽  
Paul Ullrich ◽  
Peter Gleckler ◽  
...  
Keyword(s):  
High Resolution ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Climate Model ◽  
Daily Precipitation ◽  
Flash Flood ◽  
Global Climate ◽  
Global Climate Model ◽  
Model Performance ◽  
Horizontal Resolution

We examine the resolution dependence of errors in extreme sub-daily precipitation in available high-resolution climate models. We find that simulated extreme precipitation increases as horizontal resolution increases but that appropriately constructed model skill metrics do not significantly change. We find little evidence that simulated extreme winter or summer storm processes significantly improve with the resolution because the model performance changes identified are consistent with expectations from scale dependence arguments alone. We also discuss the implications of these scale-dependent limitations on the interpretation of simulated extreme precipitation. This article is part of a discussion meeting issue ‘Intensification of short-duration rainfall extremes and implications for flash flood risks’.

The response of Northern Hemisphere polar lows to2climate change in a 25 km high-resolution global climate model

2020 ◽  
Author(s):  
Len Shaffrey ◽  
Helene Bresson ◽  
Kevin Hodges ◽  
Giuseppe Zappa
Keyword(s):  
High Resolution ◽  
Northern Hemisphere ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Heavy Precipitation ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Polar Lows

<p>Polar lows are small, intense cyclones that form at high latitudes during winter. Their high wind speeds and heavy precipitation can have substantial impacts on shipping, coastal communities and infrastructure. However, climate models typically have low resolutions and therefore poorly simulate Polar Lows. This reduces the confidence that can be placed in future projections of extreme high latitude weather and associated risks.</p><p>In this study, Polar Lows are assessed for the first time in a high-resolution (25 km) global climate atmosphere-only model, N512 HadGEM3-GA3, for both present-day and future RCP 8.5 climate scenarios. Using an objective tracking algorithm, the representation of Polar Lows in the N512 HadGEM3-GA3 present-day simulation is found to agree reasonably well the NCEP-CFS reanalysis. RCP8.5 scenario conditions are generated by adding SST changes between 1990-2010 and 2090-2110 from the RCP8.5 experiments with the HadGEM2-ES model to observed SSTs from the present-day climate. In the RCP8.5 N512 HadGEM-GA3 simulations, the number of Northern Hemisphere Polar Lows are projected to substantially decrease (by over 60%) by the end of the 21st century, which is largely due to an increase in atmospheric static stability. However, new regions of Polar Low activity along the northern Russian coastlines are found where the Arctic sea ice is projected to retreat.</p>

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.

The MJO-QBO Relationship in a GCM with Stratospheric Nudging

2021 ◽  
pp. 1-69
Author(s):  
Zane Martin ◽  
Clara Orbe ◽  
Shuguang Wang ◽  
Adam Sobel
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Global Climate Models ◽  
Boreal Winter ◽  
Quasi Biennial Oscillation ◽  
Meridional Winds ◽  
Goddard Institute ◽  
Minimal Bias

AbstractObservational studies show a strong connection between the intraseasonal Madden-Julian oscillation (MJO) and the stratospheric quasi-biennial oscillation (QBO): the boreal winter MJO is stronger, more predictable, and has different teleconnections when the QBO in the lower stratosphere is easterly versus westerly. Despite the strength of the observed connection, global climate models do not produce an MJO-QBO link. Here the authors use a current-generation ocean-atmosphere coupled NASA Goddard Institute for Space Studies global climate model (Model E2.1) to examine the MJO-QBO link. To represent the QBO with minimal bias, the model zonal mean stratospheric zonal and meridional winds are relaxed to reanalysis fields from 1980-2017. The model troposphere, including the MJO, is allowed to freely evolve. The model with stratospheric nudging captures QBO signals well, including QBO temperature anomalies. However, an ensemble of nudged simulations still lacks an MJO-QBO connection.

scholarly journals Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in the EC-Earth global climate model

2017 ◽  
Vol 10 (3) ◽  
pp. 1383-1402 ◽  
Author(s):  
Paolo Davini ◽  
Jost von Hardenberg ◽  
Susanna Corti ◽  
Hannah M. Christensen ◽  
Stephan Juricke ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Rainfall Variability ◽  
Global Climate Model ◽  
Small Scale ◽  
Low Resolution ◽  
The Impact ◽  
Stochastic Physics

Abstract. The Climate SPHINX (Stochastic Physics HIgh resolutioN eXperiments) project is a comprehensive set of ensemble simulations aimed at evaluating the sensitivity of present and future climate to model resolution and stochastic parameterisation. The EC-Earth Earth system model is used to explore the impact of stochastic physics in a large ensemble of 30-year climate integrations at five different atmospheric horizontal resolutions (from 125 up to 16 km). The project includes more than 120 simulations in both a historical scenario (1979–2008) and a climate change projection (2039–2068), together with coupled transient runs (1850–2100). A total of 20.4 million core hours have been used, made available from a single year grant from PRACE (the Partnership for Advanced Computing in Europe), and close to 1.5 PB of output data have been produced on SuperMUC IBM Petascale System at the Leibniz Supercomputing Centre (LRZ) in Garching, Germany. About 140 TB of post-processed data are stored on the CINECA supercomputing centre archives and are freely accessible to the community thanks to an EUDAT data pilot project. This paper presents the technical and scientific set-up of the experiments, including the details on the forcing used for the simulations performed, defining the SPHINX v1.0 protocol. In addition, an overview of preliminary results is given. An improvement in the simulation of Euro-Atlantic atmospheric blocking following resolution increase is observed. It is also shown that including stochastic parameterisation in the low-resolution runs helps to improve some aspects of the tropical climate – specifically the Madden–Julian Oscillation and the tropical rainfall variability. These findings show the importance of representing the impact of small-scale processes on the large-scale climate variability either explicitly (with high-resolution simulations) or stochastically (in low-resolution simulations).

scholarly journals Assessing the impact of global warming on worldwide open field tomato cultivation through CSIRO-Mk3·0 global climate model

2016 ◽  
Vol 155 (3) ◽  
pp. 407-420 ◽  
Author(s):  
R. S. SILVA ◽  
L. KUMAR ◽  
F. SHABANI ◽  
M. C. PICANÇO
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Open Field ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Current Model ◽  
Global Climate Models ◽  
The Impact

SUMMARYTomato (Solanum lycopersicum L.) is one of the most important vegetable crops globally and an important agricultural sector for generating employment. Open field cultivation of tomatoes exposes the crop to climatic conditions, whereas greenhouse production is protected. Hence, global warming will have a greater impact on open field cultivation of tomatoes rather than the controlled greenhouse environment. Although the scale of potential impacts is uncertain, there are techniques that can be implemented to predict these impacts. Global climate models (GCMs) are useful tools for the analysis of possible impacts on a species. The current study aims to determine the impacts of climate change and the major factors of abiotic stress that limit the open field cultivation of tomatoes in both the present and future, based on predicted global climate change using CLIMatic indEX and the A2 emissions scenario, together with the GCM Commonwealth Scientific and Industrial Research Organisation (CSIRO)-Mk3·0 (CS), for the years 2050 and 2100. The results indicate that large areas that currently have an optimum climate will become climatically marginal or unsuitable for open field cultivation of tomatoes due to progressively increasing heat and dry stress in the future. Conversely, large areas now marginal and unsuitable for open field cultivation of tomatoes will become suitable or optimal due to a decrease in cold stress. The current model may be useful for plant geneticists and horticulturalists who could develop new regional stress-resilient tomato cultivars based on needs related to these modelling projections.

Impact of heterogeneous chemistry on the distribution of Glyoxal and Methylglyoxal in the troposphere

2021 ◽  
Author(s):  
Ramiro Checa-Garcia ◽  
Didier Didier Hauglustaine ◽  
Yves Balkanski ◽  
Paola Formenti
Keyword(s):  
Atmospheric Chemistry ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Experimental Simulation ◽  
Heterogeneous Chemistry ◽  
Closed Set ◽  
Sensitivity Studies ◽  
The Tropics

<p>Glyoxal (GL) and methylglyoxal (MGL) are the smallest di-carbonyls present in the atmosphere. They hydrate easily, a process that is followed by an oligomerisation. As a consequence, it is considered that they participate actively in the formation of secondary organic aerosols (SOA) and therefore, they are being introduced in the current climate models with interactive chemistry to assess their importance on atmospheric chemistry. In our study we present the introduction of glyoxal in the INCA global model. A new closed set of gas-phase  reactions is analysed first with a box model. Then the simulated global distribution of glyoxal by the global climate model is compared with satellite observations. We show that the oxidation of volatile organic compounds and acetylene, together with the photolysis of more complex di-carbonyls allows us to reproduce well glyoxal seasonal cycle in the tropics but it requires an additional sink in several northern hemispheric regions. Additional sensitivity studies are being conducted by introducing  GL and MGL interactions with dust and SOA according to new uptake  coefficients obtained by dedicated experiments in the CESAM instrument (Chamber of Experimental Simulation of Atmospheric Multiphases). The effects of these heterogeneous chemistry processes will be quantified in the light of the new chamber measurements  and also evaluated in terms of optical properties of aged dust aerosol  and the changes in direct radiative effects  of the involved aerosol species.</p>

How detailed do cloud microphysics need to be in climate models?

2021 ◽  
Author(s):  
Ulrike Proske ◽  
Sylvaine Ferrachat ◽  
David Neubauer ◽  
Ulrike Lohmann
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Computing Time ◽  
Cloud Microphysics ◽  
Model Response ◽  
Microphysical Processes ◽  
Improved Accuracy

<p>Clouds are of major importance for the climate system, but the radiative forcing resulting from their interaction with aerosols remains uncertain. To improve the representation of clouds in climate models, the parameterisations of cloud microphysical processes (CMPs) have become increasingly detailed. However, more detailed climate models do not necessarily result in improved accuracy for estimates of radiative forcing (Knutti and Sedláček, 2013; Carslaw et al., 2018). On the contrary, simpler formulations are cheaper, sufficient for some applications, and allow for an easier understanding of the respective process' effect in the model.</p><p>This study aims to gain an understanding which CMP parameterisation complexity is sufficient through simplification. We gradually phase out processes such as riming or aggregation from the global climate model ECHAM-HAM, meaning that the processes are only allowed to exhibit a fraction of their effect on the model state. The shape of the model response as a function of the artificially scaled effect of a given process helps to understand the importance of this process for the model response and its potential for simplification. For example, if partially removing a process induces only minor alterations in the present day climate, this process presents as a good candidate for simplification. This may be then further investigated, for example in terms of computing time.<br>The resulting sensitivities to CMP complexity are envisioned to guide CMP model simplifications as well as steer research towards those processes where a more accurate representation proves to be necessary.</p><p> </p><p><br>Carslaw, Kenneth, Lindsay Lee, Leighton Regayre, and Jill Johnson (Feb. 2018). “Climate Models Are Uncertain, but We Can Do Something About It”. In: Eos 99. doi: 10.1029/2018EO093757</p><p>Knutti, Reto and Jan Sedláček (Apr. 2013). “Robustness and Uncertainties in the New CMIP5 Climate Model Projections”. In: Nature Climate Change 3.4, pp. 369–373. doi: 10.1038/nclimate1716</p>

scholarly journals Fidelity of the Observational/Reanalysis Datasets and Global Climate Models in Representation of Extreme Precipitation in East China

2018 ◽  
Vol 32 (1) ◽  
pp. 195-212 ◽  
Author(s):  
Sicheng He ◽  
Jing Yang ◽  
Qing Bao ◽  
Lei Wang ◽  
Bin Wang
Keyword(s):  
Extreme Precipitation ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Yangtze River Basin ◽  
Global Climate Model ◽  
Global Climate Models ◽  
Global Ocean ◽  
East China ◽  
Cmip5 Models

AbstractRealistic reproduction of historical extreme precipitation has been challenging for both reanalysis and global climate model (GCM) simulations. This work assessed the fidelities of the combined gridded observational datasets, reanalysis datasets, and GCMs [CMIP5 and the Chinese Academy of Sciences Flexible Global Ocean–Atmospheric Land System Model–Finite-Volume Atmospheric Model, version 2 (FGOALS-f2)] in representing extreme precipitation over East China. The assessment used 552 stations’ rain gauge data as ground truth and focused on the probability distribution function of daily precipitation and spatial structure of extreme precipitation days. The TRMM observation displays similar rainfall intensity–frequency distributions as the stations. However, three combined gridded observational datasets, four reanalysis datasets, and most of the CMIP5 models cannot capture extreme precipitation exceeding 150 mm day−1, and all underestimate extreme precipitation frequency. The observed spatial distribution of extreme precipitation exhibits two maximum centers, located over the lower-middle reach of Yangtze River basin and the deep South China region, respectively. Combined gridded observations and JRA-55 capture these two centers, but ERA-Interim, MERRA, and CFSR and almost all CMIP5 models fail to capture them. The percentage of extreme rainfall in the total rainfall amount is generally underestimated by 25%–75% in all CMIP5 models. Higher-resolution models tend to have better performance, and physical parameterization may be crucial for simulating correct extreme precipitation. The performances are significantly improved in the newly released FGOALS-f2 as a result of increased resolution and a more realistic simulation of moisture and heating profiles. This work pinpoints the common biases in the combined gridded observational datasets and reanalysis datasets and helps to improve models’ simulation of extreme precipitation, which is critically important for reliable projection of future changes in extreme precipitation.

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