scholarly journals Precipitation over southern Africa: Is there consensus among GCMs, RCMs and observational data?

2021 ◽  
Author(s):  
Maria Chara Karypidou ◽  
Eleni Katragkou ◽  
Stefan Pieter Sobolowski
Keyword(s):  
Climate Change ◽  
Southern Africa ◽  
Regional Climate ◽  
Coupled Model ◽  
Added Value ◽  
Rain Gauges ◽  
Climate Simulations ◽  
Observational Uncertainty ◽  
Direct Contrast ◽  
Improved Performance

Abstract. The region of southern Africa (SAF) is highly vulnerable to the impacts of climate change and is projected to experience severe precipitation shortages in the coming decades. Ensuring that our modelling tools are fit for the purpose of assessing these changes is critical. In this work we compare a range of satellite products along with gauge-based datasets. Additionally, we investigate the behaviour of regional climate simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX) – Africa domain, along with simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) and Phase 6 (CMIP6). We identify considerable variability in the standard deviation of precipitation between satellite products that merge with rain gauges and satellite products that do not, during the rainy season (Oct–Mar), indicating high observational uncertainty for specific regions over SAF. Good agreement both in spatial pattern and the strength of the calculated trends is found between satellite and gauge-based products, however. Both CORDEX-Africa and CMIP5 ensembles underestimate the observed trends during the analysis period. The CMIP6 ensemble displayed persistent drying trends, in direct contrast to the observations. The regional ensemble exhibited improved performance compared to its forcing (CMIP5), when the annual cycle and the extreme precipitation indices were examined, confirming the added value of the higher resolution regional climate simulations. The CMIP6 ensemble displayed a similar behaviour to CMIP5, however reducing slightly the ensemble spread. However, we show that reproduction of some key SAF phenomena, like the Angolan Low (which exerts a strong influence on regional precipitation), still poses a challenge for the global and regional models. This is likely a result of the complex climatic process that take place. Improvements in observational networks (both in-situ and satellite), as well as continued advancements in high-resolution modelling will be critical, in order to develop a robust assessment of climate change for southern Africa.

scholarly journals Incorrect Asian aerosols affecting the attribution and projection of regional climate change in CMIP6 models

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Zhili Wang ◽  
Lei Lin ◽  
Yangyang Xu ◽  
Huizheng Che ◽  
Xiaoye Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
Radiative Forcing ◽  
Impact Analysis ◽  
Climate Model ◽  
Regional Climate ◽  
Eastern China ◽  
Coupled Model ◽  
Regional Climate Change ◽  
Anthropogenic Aerosol ◽  
Wide Range

AbstractAnthropogenic aerosol (AA) forcing has been shown as a critical driver of climate change over Asia since the mid-20th century. Here we show that almost all Coupled Model Intercomparison Project Phase 6 (CMIP6) models fail to capture the observed dipole pattern of aerosol optical depth (AOD) trends over Asia during 2006–2014, last decade of CMIP6 historical simulation, due to an opposite trend over eastern China compared with observations. The incorrect AOD trend over China is attributed to problematic AA emissions adopted by CMIP6. There are obvious differences in simulated regional aerosol radiative forcing and temperature responses over Asia when using two different emissions inventories (one adopted by CMIP6; the other from Peking university, a more trustworthy inventory) to driving a global aerosol-climate model separately. We further show that some widely adopted CMIP6 pathways (after 2015) also significantly underestimate the more recent decline in AA emissions over China. These flaws may bring about errors to the CMIP6-based regional climate attribution over Asia for the last two decades and projection for the next few decades, previously anticipated to inform a wide range of impact analysis.

scholarly journals Water Budgets of Managed Forests in Northeast Germany under Climate Change—Results from a Model Study on Forest Monitoring Sites

2021 ◽  
Vol 11 (5) ◽  
pp. 2403
Author(s):  
Daniel Ziche ◽  
Winfried Riek ◽  
Alexander Russ ◽  
Rainer Hentschel ◽  
Jan Martin
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
Coupled Model ◽  
Regional Climate Models ◽  
Realistic Model ◽  
Forest Monitoring ◽  
Climate Change Scenarios ◽  
Historical Time ◽  
Time Period

To develop measures to reduce the vulnerability of forests to drought, it is necessary to estimate specific water balances in sites and to estimate their development with climate change scenarios. We quantified the water balance of seven forest monitoring sites in northeast Germany for the historical time period 1961–2019, and for climate change projections for the time period 2010–2100. We used the LWF-BROOK90 hydrological model forced with historical data, and bias-adjusted data from two models of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) downscaled with regional climate models under the representative concentration pathways (RCPs) 2.6 and 8.5. Site-specific monitoring data were used to give a realistic model input and to calibrate and validate the model. The results revealed significant trends (evapotranspiration, dry days (actual/potential transpiration < 0.7)) toward drier conditions within the historical time period and demonstrate the extreme conditions of 2018 and 2019. Under RCP8.5, both models simulate an increase in evapotranspiration and dry days. The response of precipitation to climate change is ambiguous, with increasing precipitation with one model. Under RCP2.6, both models do not reveal an increase in drought in 2071–2100 compared to 1990–2019. The current temperature increase fits RCP8.5 simulations, suggesting that this scenario is more realistic than RCP2.6.

scholarly journals Configuration and intercomparison of deep learning neural models for statistical downscaling

2020 ◽  
Vol 13 (4) ◽  
pp. 2109-2124 ◽  
Author(s):  
Jorge Baño-Medina ◽  
Rodrigo Manzanas ◽  
José Manuel Gutiérrez
Keyword(s):  
Climate Change ◽  
Deep Learning ◽  
Statistical Downscaling ◽  
Linear Models ◽  
Regional Climate ◽  
Added Value ◽  
Climate Conditions ◽  
Continental Scale ◽  
Spatial Features ◽  
Learning Techniques

Abstract. Deep learning techniques (in particular convolutional neural networks, CNNs) have recently emerged as a promising approach for statistical downscaling due to their ability to learn spatial features from huge spatiotemporal datasets. However, existing studies are based on complex models, applied to particular case studies and using simple validation frameworks, which makes a proper assessment of the (possible) added value offered by these techniques difficult. As a result, these models are usually seen as black boxes, generating distrust among the climate community, particularly in climate change applications. In this paper we undertake a comprehensive assessment of deep learning techniques for continental-scale statistical downscaling, building on the VALUE validation framework. In particular, different CNN models of increasing complexity are applied to downscale temperature and precipitation over Europe, comparing them with a few standard benchmark methods from VALUE (linear and generalized linear models) which have been traditionally used for this purpose. Besides analyzing the adequacy of different components and topologies, we also focus on their extrapolation capability, a critical point for their potential application in climate change studies. To do this, we use a warm test period as a surrogate for possible future climate conditions. Our results show that, while the added value of CNNs is mostly limited to the reproduction of extremes for temperature, these techniques do outperform the classic ones in the case of precipitation for most aspects considered. This overall good performance, together with the fact that they can be suitably applied to large regions (e.g., continents) without worrying about the spatial features being considered as predictors, can foster the use of statistical approaches in international initiatives such as Coordinated Regional Climate Downscaling Experiment (CORDEX).

Realised added value in dynamical downscaling of Australian climate change

2021 ◽  
Author(s):  
Giovanni Di Virgilio ◽  
Jason P. Evans ◽  
Alejandro Di Luca ◽  
Michael R. Grose ◽  
Vanessa Round ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Adaptation ◽  
Regional Climate ◽  
Future Climate ◽  
Added Value ◽  
Climate Projections ◽  
Eastern Australia ◽  
Australian Alps ◽  
Future Climate Projections

&lt;p&gt;Coarse resolution global climate models (GCM) cannot resolve fine-scale drivers of regional climate, which is the scale where climate adaptation decisions are made. Regional climate models (RCMs) generate high-resolution projections by dynamically downscaling GCM outputs. However, evidence of where and when downscaling provides new information about both the current climate (added value, AV) and projected climate change signals, relative to driving data, is lacking. Seasons and locations where CORDEX-Australasia ERA-Interim and GCM-driven RCMs show AV for mean and extreme precipitation and temperature are identified. A new concept is introduced, &amp;#8216;realised added value&amp;#8217;, that identifies where and when RCMs simultaneously add value in the present climate and project a different climate change signal, thus suggesting plausible improvements in future climate projections by RCMs. ERA-Interim-driven RCMs add value to the simulation of summer-time mean precipitation, especially over northern and eastern Australia. GCM-driven RCMs show AV for precipitation over complex orography in south-eastern Australia during winter and widespread AV for mean and extreme minimum temperature during both seasons, especially over coastal and high-altitude areas. RCM projections of decreased winter rainfall over the Australian Alps and decreased summer rainfall over northern Australia are collocated with notable realised added value. Realised added value averaged across models, variables, seasons and statistics is evident across the majority of Australia and shows where plausible improvements in future climate projections are conferred by RCMs. This assessment of varying RCM capabilities to provide realised added value to GCM projections can be applied globally to inform climate adaptation and model development.&lt;/p&gt;

On the added value of the regional climate model REMO in the assessment of climate change signal over Central Africa

2017 ◽  
Vol 49 (11-12) ◽  
pp. 3813-3838 ◽  
Author(s):  
Thierry C. Fotso-Nguemo ◽  
Derbetini A. Vondou ◽  
Wilfried M. Pokam ◽  
Zéphirin Yepdo Djomou ◽  
Ismaïla Diallo ◽  
...  
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Central Africa ◽  
Added Value ◽  
Climate Change Signal

Large-scale drivers of the Mediterranean climate change hot-spot

2021 ◽  
Author(s):  
Roman Brogli ◽  
Silje Lund Sørland ◽  
Nico Kröner ◽  
Christoph Schär
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Hot Spot ◽  
Regional Climate ◽  
Lapse Rate ◽  
Summer Climate ◽  
Climate Simulations ◽  
Summer Warming ◽  
The Mediterranean ◽  
Circulation Changes

&lt;div&gt; &lt;p&gt;&lt;span&gt;It has long been recognized that the Mediterranean is a &amp;#8216;hot-spot&amp;#8217; of climate change. The model-projected year-round precipitation decline and amplified summer warming are among the leading causes of the vulnerability of the Mediterranean to greenhouse gas-driven warming. We investigate large-scale drivers influencing both the Mediterranean drying and summer warming in regional climate simulations. To isolate the influence of multiple large-scale drivers, we sequentially add the respective drivers from global models to regional climate model simulations. Additionally, we confirm the robustness of our results across multiple ensembles of global and regional climate simulations.&lt;/span&gt;&lt;/p&gt; &lt;/div&gt;&lt;div&gt; &lt;p&gt;&lt;span&gt;We will present in detail how changes in the atmospheric stratification are key in causing the amplified Mediterranean summer warming. Together with the land-ocean warming contrast, stratification changes also drive the summer precipitation decline. Summer circulation changes generally have a surprisingly small influence on the changing Mediterranean summer climate. In contrast, changes in the circulation are the primary driver for the projected winter precipitation decline. Since land-ocean contrast and stratification changes are more robust in global climate simulations than circulation changes, we argue that the uncertainty associated with the projected climate change patterns should be considered smaller in summer than in winter.&lt;/span&gt;&lt;/p&gt; &lt;/div&gt;&lt;div&gt; &lt;p&gt;&lt;span&gt;References:&lt;/span&gt;&lt;/p&gt; &lt;/div&gt;&lt;div&gt; &lt;p&gt;&lt;span&gt;Brogli, R., S. L. S&amp;#248;rland, N. Kr&amp;#246;ner, and C. Sch&amp;#228;r, 2019: Causes of future Mediterranean precipitation decline depend on the season. Environmental Research Letters, 14, 114017, doi:10.1088/1748-9326/ab4438.&lt;/span&gt;&lt;/p&gt; &lt;/div&gt;&lt;div&gt; &lt;p&gt;&lt;span&gt;Brogli, R., N. Kr&amp;#246;ner, S. L. S&amp;#248;rland, D. L&amp;#252;thi and C. Sch&amp;#228;r, 2019: The Role of Hadley Circulation and Lapse-Rate Changes for the Future European Summer Climate. Journal of Climate, 32, 385-404, doi:10.1175/JCLI-D-18-0431.1&lt;/span&gt;&lt;/p&gt; &lt;/div&gt;

scholarly journals Toward Assessing NARCCAP Regional Climate Model Credibility for the North American Monsoon: Future Climate Simulations*

2015 ◽  
Vol 28 (17) ◽  
pp. 6707-6728 ◽  
Author(s):  
Melissa S. Bukovsky ◽  
Carlos M. Carrillo ◽  
David J. Gochis ◽  
Dorit M. Hammerling ◽  
Rachel R. McCrary ◽  
...  
Keyword(s):  
Climate Change ◽  
North American ◽  
Southern Oscillation ◽  
Monsoon Season ◽  
Regional Climate ◽  
Global Climate Models ◽  
North American Monsoon ◽  
The North ◽  
Climate Simulations ◽  
Projected Changes

Abstract This study presents climate change results from the North American Regional Climate Change Assessment Program (NARCCAP) suite of dynamically downscaled simulations for the North American monsoon system in the southwestern United States and northwestern Mexico. The focus is on changes in precipitation and the processes driving the projected changes from the regional climate simulations and their driving coupled atmosphere–ocean global climate models. The effect of known biases on the projections is also examined. Overall, there is strong ensemble agreement for a large decrease in precipitation during the monsoon season; however, this agreement and the magnitude of the ensemble-mean change is likely deceiving, as the greatest decreases are produced by the simulations that are the most biased in the baseline/current climate. Furthermore, some of the greatest decreases in precipitation are being driven by changes in processes/phenomena that are less credible (e.g., changes in El Niño–Southern Oscillation, when it is initially not simulated well). In other simulations, the processes driving the precipitation change may be plausible, but other biases (e.g., biases in low-level moisture or precipitation intensity) appear to be affecting the magnitude of the projected changes. The most and least credible simulations are clearly identified, while the other simulations are mixed in their abilities to produce projections of value.

Regional climate simulations at kilometer-scale with RegCM4: Evaluation of precipitation and future projections

2020 ◽  
Author(s):  
Paolo Stocchi ◽  
Emanuela Pichelli ◽  
Erika Coppola ◽  
Jose Abraham Torres Alvarez ◽  
Filippo Giorgi
Keyword(s):  
Global Climate Model ◽  
Regional Climate ◽  
Added Value ◽  
Historical Period ◽  
Climate Projections ◽  
Model Errors ◽  
Grid Spacing ◽  
Climate Simulations ◽  
Near Future ◽  
Far Future

&lt;p&gt;The recent increase in climate modeling activities at convection permitting scales (grid spacing under 4 km) has strongly been motivated by the increased computer capacities in the last years with the aim to reduce the model errors associated with parameterized convection and a more detailed representation of present and future regional climate. Some Regional climate projects addressing on convection permitting modeling simulations and projections have been recently implemented to make more robust conclusions on the added value of convection permitting simulation to future climate projections. Here, we present convection resolving climate simulations performed in the framework the European Climate Prediction System (EUCP) project, using the non-hydrostatic version of the RegCM model. The RegCM simulations have a grid spacing of 3 km, over three different regions (Pan-Alpine, Central Europe, and South-East Europe). These simulations were driven by initial and boundary conditions built from intermediate 12 km simulations driven by the global climate model (GCM) HadGEM2-ES. We considered three time slices each one of them covering a 10-year period, the historical (1996-2005), the near future (2041-2050) and the far future (2090-2099) under the RCP8.5 scenario. The high resolutions (3 km) simulations, over the historical period, are evaluated through comparison with available observations data sets (including in-situ and satellite-based observation of precipitation) and coarse resolution (12 km) simulation is used as benchmark. The kilometer-scale RegCM4.7 scenario (RCP8.5) simulations, driven by HadGEM2-ES, near future (2041-2050) and the far future (2090-2099), are also analyzed and presented, focusing on the future change in terms of mean precipitation, precipitation intensity and frequency and heavy precipitation on daily and hourly timescales in different seasons.&lt;/p&gt;

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