A Weather-Type Classification and Its Application to Near-Surface Wind Climate Change Projections over the Adriatic Region

The main goal of this study is to present a recently developed classification method for weather types based on the vorticity and the location of the synoptic centers relative to the Adriatic region. The basis of the present objective classification, applied to the Adriatic region, is the subjective classification developed by Poje. Our algorithm considered daily mean sea-level pressure and 500 hPa geopotential height to define one out of 17 possible weather types. We applied the algorithm to identify which weather type was relevant in the generation of the two typical near-surface winds over the Adriatic region, namely Bora and Sirocco. Two high-resolution (0.11°) EURO-CORDEX regional climate models were used, SMHI-RCA4 and DHMZ-RegCM4, forced by several CMIP5 global climate models and analyzed for two 30-year periods: near-present day and mid-21st century climate conditions under the high-end Representative Concentration Pathway (RCP8.5) scenario. Bora and Sirocco days were extracted for each weather type and a distribution over the 30-year period was presented. Our results suggest that in the winter season, climate model projections indicate a reduction in the main cyclonic types relevant in the formation of Bora over the entire Adriatic region and an increase in the number of anticyclonic types relevant in Sirocco events. In contrast, for the summer season, an increase in the main anticyclonic Bora-related weather types is found in the ensemble over the northern Adriatic region.

Download Full-text

The Surface-Pressure Signature of Atmospheric Tides in Modern Climate Models

Journal of the Atmospheric Sciences ◽

10.1175/2010jas3560.1 ◽

2011 ◽

Vol 68 (3) ◽

pp. 495-514 ◽

Cited By ~ 11

Author(s):

Curt Covey ◽

Aiguo Dai ◽

Dan Marsh ◽

Richard S. Lindzen

Keyword(s):

Surface Pressure ◽

Climate Models ◽

Climate Model ◽

Global Climate ◽

Global Climate Models ◽

Atmospheric Tides ◽

Intergovernmental Panel ◽

Near Surface ◽

Low Altitude ◽

Upper Boundary

Abstract Although atmospheric tides driven by solar heating are readily detectable at the earth’s surface as variations in air pressure, their simulations in current coupled global climate models have not been fully examined. This work examines near-surface-pressure tides in climate models that contributed to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC); it compares them with tides both from observations and from the Whole Atmosphere Community Climate Model (WACCM), which extends from the earth’s surface to the thermosphere. Surprising consistency is found among observations and all model simulations, despite variation of the altitudes of model upper boundaries from 32 to 76 km in the IPCC models and at 135 km for WACCM. These results are consistent with previous suggestions that placing a model’s upper boundary at low altitude leads to partly compensating errors—such as reducing the forcing of the tides by ozone heating, but also introducing spurious waves at the upper boundary, which propagate to the surface.

Download Full-text

Balanced estimate and uncertainty assessment of European climate change using the large EURO-CORDEX regional climate model ensemble

10.5194/esd-2021-8 ◽

2021 ◽

Author(s):

Guillaume Evin ◽

Samuel Somot ◽

Benoit Hingray

Keyword(s):

Regional Climate Model ◽

Climate Models ◽

Climate Model ◽

Global Climate ◽

Regional Climate ◽

Uncertainty Assessment ◽

Global Climate Models ◽

Climate Projections ◽

Total Uncertainty ◽

Near Surface

Abstract. Large Multiscenarios Multimodel Ensembles (MMEs) of regional climate model (RCM) experiments driven by Global Climate Models (GCM) are made available worldwide and aim at providing robust estimates of climate changes and associated uncertainties. Due to many missing combinations of emission scenarios and climate models leading to sparse Scenario-GCM-RCM matrices, these large ensembles are however very unbalanced, which makes uncertainty analyses impossible with standard approaches. In this paper, the uncertainty assessment is carried out by applying an advanced statistical approach, called QUALYPSO, to a very large ensemble of 87 EURO-CORDEX climate projections, the largest ensemble ever produced for regional projections in Europe. This analysis provides i) the most up-to-date and balanced estimates of mean changes for near-surface temperature and precipitation in Europe, ii) the total uncertainty of projections and its partition as a function of time, and iii) the list of the most important contributors to the model uncertainty. For changes of total precipitation and mean temperature in winter (DJF) and summer (JJA), the uncertainty due to RCMs can be as large as the uncertainty due to GCMs at the end of the century (2071–2099). Both uncertainty sources are mainly due to a small number of individual models clearly identified. Due to the highly unbalanced character of the MME, mean estimated changes can drastically differ from standard average estimates based on the raw ensemble of opportunity. For the RCP4.5 emission scenario in Central-Eastern Europe for instance, the difference between balanced and direct estimates are up to 0.8 °C for summer temperature changes and up to 20 % for summer precipitation changes at the end of the century.

Download Full-text

Large sensitivity of a Greenland ice sheet model to atmospheric forcing fields

The Cryosphere Discussions ◽

10.5194/tcd-6-1037-2012 ◽

2012 ◽

Vol 6 (2) ◽

pp. 1037-1083 ◽

Cited By ~ 3

Author(s):

A. Quiquet ◽

H. J. Punge ◽

C. Ritz ◽

X. Fettweis ◽

M. Kageyama ◽

...

Keyword(s):

General Circulation ◽

Climate Models ◽

Climate Model ◽

Ice Sheets ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Global Climate Models ◽

Near Surface ◽

Temperature And Precipitation ◽

The Impact

Abstract. The prediction of future climate and ice sheet evolution requires coupling of ice sheet and climate models. Before proceeding to a coupled setup, we propose to analyze the impact of model simulated climate on an ice sheet. Here, we undertake this exercise for a set of regional and global climate models. Modelled near surface air temperature and precipitation are provided as upper boundary condition to the GRISLI (GRenoble Ice Shelf and Land Ice model) hybrid ice sheet model (ISM) in its Greenland configuration. After 20 kyr of simulation, the resulting ice sheets highlight the differences between the climate models. While modelled ice sheet sizes are generally comparable to the observed ones, there are considerable deviations among the ice sheets on regional scales. These can be explained by difficulties in modelling local temperature and precipitation near the coast. This is especially true in the case of global models. But the deviations of each climate model are also due to the differences in the atmospheric general circulation. In the context of coupling ice sheet and climate models, we conclude that appropriate downscaling methods will be needed and systematic corrections of the climatic variables at the interface may be required in some cases to obtain realistic results for the Greenland ice sheet (GIS).

Download Full-text

Precipitation Associated with Cyclogenetic Hotspot Regions in the Extratropical Southern Hemisphere: CORDEX-CORE Projections

10.5194/egusphere-egu2020-3147 ◽

2020 ◽

Author(s):

Michelle Reboita ◽

Marco Reale ◽

Rosmeri da Rocha ◽

Graziano Giuliani ◽

Erika Coppola ◽

...

Keyword(s):

Southern Hemisphere ◽

Climate Models ◽

Climate Model ◽

Global Climate ◽

Regional Climate ◽

Winter Season ◽

Coupled Model ◽

Global Climate Models ◽

Precipitation Intensity ◽

Southeastern Australia

Projections of the precipitation associated with cyclones in the main cyclogenetic regions of the Extratropical Southern Hemisphere domains (Africa - AFR, Australia - AUS and South America - SAM) are here analyzed during the winter season (JJA). The projections were obtained with the Regional Climate Model version 4 (RegCM4) nested in three global climate models (GCMs) from the Coupled Model Intercomparison Project phase 5 (CMIP5) under the Representative Concentration Pathway 8.5. RegCM4 simulations were executed with horizontal grid spacing of 25 km and for the period 1979-2100. As reference period, we consider the interval 1995-2014 and as future climate, the period 2080-2099. Cyclones are identified using an algorithm based on the neighbor nearest approach applied to 6 hourly mean sea level pressure (SLP) fields. In SAM and AUS domains, two hotspot regions for cyclogenesis are selected while for AFR only one is considered. First, in each hotspot region, the cyclogeneses are identified and, then, the mean precipitation from the previous day (day-1) to the day after (day+1) of these processes is calculated. A general negative trend in the cyclone's frequency is projected for the period 2080-2099. However, for the same period, it is projected an increase of precipitation intensity for AFR domain, mainly near the southwestern coast of the continent. In AUS the increase is observed between southeastern Australia and New Zeland, and over north New Zealand. For SAM there is an expansion of the area with a maximum precipitation intensity close to southern Brazil and Uruguay and to the east of 60oW near 40oS. Summarizing, the precipitation associated with individual cyclones will increase on average in the future (for example 30% in the SAM domain), being the storms less frequent but more intense.

Download Full-text

Near-surface wind variability over the broader Adriatic region: insights from an ensemble of regional climate models

Climate Dynamics ◽

10.1007/s00382-017-3885-5 ◽

2017 ◽

Vol 50 (11-12) ◽

pp. 4455-4480 ◽

Cited By ~ 16

Author(s):

Andreina Belušić ◽

Maja Telišman Prtenjak ◽

Ivan Güttler ◽

Nikolina Ban ◽

David Leutwyler ◽

...

Keyword(s):

Climate Models ◽

Regional Climate ◽

Surface Wind ◽

Regional Climate Models ◽

Near Surface ◽

Wind Variability ◽

Adriatic Region

Download Full-text

Balanced estimate and uncertainty assessment of European climate change using the large EURO-CORDEX regional climate model ensemble

Earth System Dynamics ◽

10.5194/esd-12-1543-2021 ◽

2021 ◽

Vol 12 (4) ◽

pp. 1543-1569

Author(s):

Guillaume Evin ◽

Samuel Somot ◽

Benoit Hingray

Keyword(s):

Regional Climate Model ◽

Climate Models ◽

Climate Model ◽

Global Climate ◽

Regional Climate ◽

Uncertainty Assessment ◽

Global Climate Models ◽

Climate Projections ◽

Total Uncertainty ◽

Near Surface

Abstract. Large multiscenario multimodel ensembles (MMEs) of regional climate model (RCM) experiments driven by global climate models (GCMs) are made available worldwide and aim at providing robust estimates of climate changes and associated uncertainties. Due to many missing combinations of emission scenarios and climate models leading to sparse scenario–GCM–RCM matrices, these large ensembles, however, are very unbalanced, which makes uncertainty analyses impossible with standard approaches. In this paper, the uncertainty assessment is carried out by applying an advanced statistical approach, called QUALYPSO, to a very large ensemble of 87 EURO-CORDEX climate projections, the largest MME based on regional climate models ever produced in Europe. This analysis provides a detailed description of this MME, including (i) balanced estimates of mean changes for near-surface temperature and precipitation in Europe, (ii) the total uncertainty of projections and its partition as a function of time, and (iii) the list of the most important contributors to the model uncertainty. For changes in total precipitation and mean temperature in winter (DJF) and summer (JJA), the uncertainty due to RCMs can be as large as the uncertainty due to GCMs at the end of the century (2071–2099). Both uncertainty sources are mainly due to a small number of individual models clearly identified. Due to the highly unbalanced character of the MME, mean estimated changes can drastically differ from standard average estimates based on the raw ensemble of opportunity. For the RCP4.5 emission scenario in central–eastern Europe for instance, the difference between balanced and direct estimates is up to 0.8 ∘C for summer temperature changes and up to 20 % for summer precipitation changes at the end of the century.

Download Full-text

Projected Changes in European and North Atlantic Seasonal Wind Climate Derived from CMIP5 Simulations

Journal of Climate ◽

10.1175/jcli-d-19-0023.1 ◽

2019 ◽

Vol 32 (19) ◽

pp. 6467-6490 ◽

Cited By ~ 8

Author(s):

Kimmo Ruosteenoja ◽

Timo Vihma ◽

Ari Venäläinen

Keyword(s):

North Atlantic ◽

Climate Models ◽

Global Climate ◽

Arctic Sea Ice ◽

Global Climate Models ◽

Near Surface ◽

Wind Speeds ◽

The North ◽

Seasonal Wind ◽

Projected Changes

Abstract Future changes in geostrophic winds over Europe and the North Atlantic region were studied utilizing output data from 21 CMIP5 global climate models (GCMs). Changes in temporal means, extremes, and the joint distribution of speed and direction were considered. In concordance with previous research, the time mean and extreme scalar wind speeds do not change pronouncedly in response to the projected climate change; some degree of weakening occurs in the majority of the domain. Nevertheless, substantial changes in high wind speeds are identified when studying the geostrophic winds from different directions separately. In particular, in northern Europe in autumn and in parts of northwestern Europe in winter, the frequency of strong westerly winds is projected to increase by up to 50%. Concurrently, easterly winds become less common. In addition, we evaluated the potential of the GCMs to simulate changes in the near-surface true wind speeds. In ocean areas, changes in the true and geostrophic winds are mainly consistent and the emerging differences can be explained (e.g., by the retreat of Arctic sea ice). Conversely, in several GCMs the continental wind speed response proved to be predominantly determined by fairly arbitrary changes in the surface properties rather than by changes in the atmospheric circulation. Accordingly, true wind projections derived directly from the model output should be treated with caution since they do not necessarily reflect the actual atmospheric response to global warming.

Download Full-text

Evaluating temperature extremes in CMIP6 simulations using statistically proper evaluation methods

10.5194/egusphere-egu21-9722 ◽

2021 ◽

Author(s):

Thordis Thorarinsdottir ◽

Jana Sillmann ◽

Marion Haugen ◽

Nadine Gissibl ◽

Marit Sandstad

Keyword(s):

Air Temperature ◽

Model Evaluation ◽

Climate Models ◽

Climate Model ◽

Mean Squared Error ◽

Surface Air Temperature ◽

Cmip5 Models ◽

Model Output ◽

Intergovernmental Panel ◽

Near Surface

Reliable projections of extremes in near-surface air temperature (SAT) by climate models become more and more important&#160;as global warming is leading to significant increases in the hottest days and decreases in coldest nights around the world with considerable impacts on various sectors, such as agriculture, health and tourism.Climate model evaluation has traditionally been performed by comparing summary statistics that are derived from simulated model output and corresponding observed quantities using, for instance, the root mean squared error (RMSE) or mean bias as also used in the model evaluation chapter of the fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). Both RMSE and mean bias compare averages over time and/or space, ignoring the variability, or the uncertainty, in the underlying values. Particularly when interested in the evaluation of climate extremes, climate models should be evaluated by comparing the probability distribution of model output to the corresponding distribution of observed data.To address this shortcoming, we use the integrated quadratic distance (IQD) to compare distributions of simulated indices to the corresponding distributions from a data product. The IQD is the proper divergence associated with the proper continuous ranked probability score (CRPS) as it fulfills essential decision-theoretic properties for ranking competing models and testing equality in performance, while also assessing the full distribution.The IQD is applied to evaluate CMIP5 and CMIP6 simulations of monthly maximum (TXx) and minimum near-surface air temperature (TNn) over the data-dense regions Europe and North America against both observational and reanalysis datasets. There is not a notable difference between the model generations CMIP5 and CMIP6 when the model simulations are compared against the observational dataset HadEX2. However, the CMIP6 models show a better agreement with the reanalysis ERA5 than CMIP5 models, with a few exceptions. Overall, the climate models show higher skill when compared against ERA5 than when compared against HadEX2. While the model rankings vary with region, season and index, the model evaluation is robust against changes in the grid resolution considered in the analysis.

Download Full-text

The MJO-QBO Relationship in a GCM with Stratospheric Nudging

Journal of Climate ◽

10.1175/jcli-d-20-0636.1 ◽

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.

Download Full-text

Regional Climate Model Inter-Comparison for Antarctica within a Data Science Framework

10.5194/egusphere-egu21-4892 ◽

2021 ◽

Author(s):

Jeremy Carter ◽

Amber Leeson ◽

Andrew Orr ◽

Christoph Kittel ◽

Melchior van Wessem

Keyword(s):

Regional Climate Model ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Regional Climate Models ◽

Future Climate Change ◽

Near Surface ◽

Virtual Lab ◽

Model Variability ◽

The Antarctic

Understanding the surface climatology of the Antarctic ice sheet is essential if we are to adequately predict its response to future climate change. This includes both primary impacts such as increased ice melting and secondary impacts such as ice shelf collapse events. Given its size, and inhospitable environment, weather stations on Antarctica are sparse. Thus, we rely on regional climate models to 1) develop our understanding of how the climate of Antarctica varies in both time and space and 2) provide data to use as context for remote sensing studies and forcing for dynamical process models. Given that there are a number of different regional climate models available that explicitly simulate Antarctic climate, understanding inter- and intra model variability is important.Here, inter- and intra-model variability in Antarctic-wide regional climate model output is assessed for: snowfall; rainfall; snowmelt and near-surface air temperature within a cloud-based virtual lab framework. State-of-the-art regional climate model runs from the Antarctic-CORDEX project using the RACMO, MAR and MetUM models are used, together with the ERA5 and ERA-Interim reanalyses products. Multiple simulations using the same model and domain boundary but run at either different spatial resolutions or with different driving data are used. Traditional analysis techniques are exploited and the question of potential added value from more modern and involved methods such as the use of Gaussian Processes is investigated. The advantages of using a virtual lab in a cloud based environment for increasing transparency and reproducibility, are demonstrated, with a view to ultimately make the code and methods used widely available for other research groups.

Download Full-text