scholarly journals Annual and semiannual cycles of midlatitude near-surface temperature and tropospheric baroclinicity: reanalysis data and AOGCM simulations

2017 ◽  
Vol 8 (2) ◽  
pp. 295-312 ◽  
Author(s):  
Valerio Lembo ◽  
Isabella Bordi ◽  
Antonio Speranza
Keyword(s):  
Surface Temperature ◽  
General Circulation ◽  
Relative Phase ◽  
North Pacific Ocean ◽  
General Circulation Models ◽  
Reanalysis Data ◽  
Seasonal Forecasts ◽  
Frequency Model ◽  
Near Surface ◽  
Annual Frequency

Abstract. Seasonal variability in near-surface air temperature and baroclinicity from the ECMWF ERA-Interim (ERAI) reanalysis and six coupled atmosphere–ocean general circulation models (AOGCMs) participating in the Coupled Model Intercomparison Project phase 3 and 5 (CMIP3 and CMIP5) are examined. In particular, the annual and semiannual cycles of hemispherically averaged fields are studied using spectral analysis. The aim is to assess the ability of coupled general circulation models to properly reproduce the observed amplitude and phase of these cycles, and investigate the relationship between near-surface temperature and baroclinicity (coherency and relative phase) in such frequency bands. The overall results of power spectra agree in displaying a statistically significant peak at the annual frequency in the zonally averaged fields of both hemispheres. The semiannual peak, instead, shows less power and in the NH seems to have a more regional character, as is observed in the North Pacific Ocean region. Results of bivariate analysis for such a region and Southern Hemisphere midlatitudes show some discrepancies between ERAI and model data, as well as among models, especially for the semiannual frequency. Specifically, (i) the coherency at the annual and semiannual frequency observed in the reanalysis data is well represented by models in both hemispheres, and (ii) at the annual frequency, estimates of the relative phase between near-surface temperature and baroclinicity are bounded between about ±15° around an average value of 220° (i.e., approximately 1-month phase shift), while at the semiannual frequency model phases show a wider dispersion in both hemispheres with larger errors in the estimates, denoting increased uncertainty and some disagreement among models. The most recent CMIP climate models (CMIP5) show several improvements when compared with CMIP3, but a degree of discrepancy still persists though masked by the large errors characterizing the semiannual frequency. These findings contribute to better characterizing the cyclic response of current global atmosphere–ocean models to the external (solar) forcing that is of interest for seasonal forecasts.

scholarly journals Annual and semiannual cycles of midlatitude surface temperature and baroclinicity: reanalysis data and AOGCMs simulations

2016 ◽  
Author(s):  
Valerio Lembo ◽  
Isabella Bordi ◽  
Antonio Speranza
Keyword(s):  
Surface Temperature ◽  
General Circulation ◽  
Relative Phase ◽  
North Pacific Ocean ◽  
General Circulation Models ◽  
Reanalysis Data ◽  
Bivariate Analysis ◽  
Seasonal Forecasts ◽  
Frequency Model ◽  
Annual Frequency

Abstract. Seasonal variability of surface air temperature and baroclinicity from the ECMWF ERA-Interim (ERAI) reanalysis and six coupled atmosphere-ocean general circulation models (AOGCMs) participating in the Coupled Model Intercomparison Project phase 3 and 5 (CMIP3 and CMIP5) are examined. In particular, the annual and semiannual cycles of hemispherically averaged fields are studied using spectral analysis. The aim is to assess the ability of coupled general circulation models to properly reproduce the observed amplitude and phase of these cycles, and investigate the relationship between surface temperature and baroclinicity (coherency and relative phase) in such frequency bands. The overall results of power spectra agree in displaying a statistically significant peak at the annual frequency in the zonally averaged fields of both hemispheres. The semiannual peak, instead, shows less power and in the NH seems to have a more regional character, as is observed in the North Pacific Ocean region. Results of bivariate analysis for such a region and Southern Hemisphere midlatitudes show some discrepancies between ERAI and model data, as well as among models, especially for the semiannual frequency. Specifically: (i) the coherency at the annual and semiannual frequency observed in the reanalysis data is well represented by models in both hemispheres; (ii) at the annual frequency, estimates of the relative phase between surface temperature and baroclinicity are bounded between about ±15° around an average value of 220° (i.e., approximately 1 month phase shift), while at the semiannual frequency model phases show a wider dispersion in both hemispheres with larger errors in the estimates, denoting increased uncertainty and some disagreement among models. The most recent CMIP climate models (CMIP5) show several improvements when compared with CMIP3 but a degree of discrepancy still persists though masked by the large errors characterizing the semiannual frequency. These findings contribute to better characterize the cyclic response of current global atmosphere-ocean models to the external (solar) forcing that is of interest for seasonal forecasts.

scholarly journals Extreme Drought Events over the Amazon Basin: The Perspective from the Reconstruction of South American Hydroclimate

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1594 ◽  
Author(s):  
Beatriz Garcia ◽  
Renata Libonati ◽  
Ana Nunes
Keyword(s):  
Surface Temperature ◽  
Extreme Events ◽  
General Circulation ◽  
Amazon Basin ◽  
General Circulation Models ◽  
Extreme Drought ◽  
Severe Drought ◽  
South American ◽  
Spatial And Temporal Patterns ◽  
Near Surface

The Amazon basin has experienced severe drought events for centuries, mainly associated with climate variability connected to tropical North Atlantic and Pacific sea surface temperature anomalous warming. Recently, these events are becoming more frequent, more intense and widespread. Because of the Amazon droughts environmental and socioeconomic impacts, there is an increased demand for understanding the characteristics of such extreme events in the region. In that regard, regional models instead of the general circulation models provide a promising strategy to generate more detailed climate information of extreme events, seeking better representation of physical processes. Due to uneven spatial distribution and gaps found in station data in tropical South America, and the need of more refined climate assessment in those regions, satellite-enhanced regional downscaling for applied studies (SRDAS) is used in the reconstruction of South American hydroclimate, with hourly to monthly outputs from January 1998. Accordingly, this research focuses on the analyses of recent extreme drought events in the years of 2005 and 2010 in the Amazon Basin, using the SRDAS monthly means of near-surface temperature and relative humidity, precipitation and vertically integrated soil moisture fields. Results from this analysis corroborate spatial and temporal patterns found in previous studies on extreme drought events in the region, displaying the distinctive features of the 2005 and 2010 drought events.

Forecast skill of autumn snow for European winter climate during the 20th century: A multi member seasonal prediction experiment

2021 ◽  
Author(s):  
Martin Wegmann ◽  
Yvan Orsolini ◽  
Antje Weisheimer ◽  
Bart van den Hurk ◽  
Gerrit Lohmann
Keyword(s):  
Snow Cover ◽  
General Circulation ◽  
Initial Conditions ◽  
Internal Variability ◽  
Seasonal Prediction ◽  
General Circulation Models ◽  
Reanalysis Data ◽  
Winter Climate ◽  
European Continent ◽  
Near Surface

<p>As the leading climate mode to explain wintertime climate variability over Europe, the North Atlantic Oscillation (NAO) has been extensively studied over the last decades. Recently, studies highlighted the state of the Northern Hemispheric cryosphere as possible predictor for the wintertime NAO (Cohen et al. 2014). Although several studies could find seasonal prediction skill in reanalysis data (Orsolini et al. 2016, Duville et al. 2017,Han & Sun 2018), experiments with ocean-atmosphere general circulation models (AOGCMs) still show conflicting results (Furtado et al. 2015, Handorf et al. 2015, Francis 2017, Gastineau et al. 2017). </p><p>Here we use two kinds ECMWF seasonal prediction ensembles starting with November initial conditions taken from the long-term reanalysis ERA-20C and forecasting the following three winter months. Besides the 110-year ensemble of 50 members representing internal variability of the atmosphere, we investigate a second ensemble of 20 members where initial conditions are split between low and high snow cover years for the Northern Hemisphere. We compare two recently used Eurasian snow cover indices for their skill in predicting winter climate for the European continent. Analyzing the two forecast experiments, we found that prediction runs starting with high snow index values in November result in significantly more negative NAO states in the following winter (DJF), which in turn modulates near surface temperatures. We track the atmospheric anomalies triggered by the high snow index through the tropo- and stratosphere as well as for the individual winter months to provide a physical explanation for the formation of this particular climate state.</p><p> </p>

Land–Ocean Shifts in Tropical Precipitation Linked to Surface Temperature and Humidity Change

2017 ◽  
Vol 30 (12) ◽  
pp. 4527-4545 ◽  
Author(s):  
F. Hugo Lambert ◽  
Angus J. Ferraro ◽  
Robin Chadwick
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Land Surface ◽  
General Circulation ◽  
General Circulation Models ◽  
Specific Humidity ◽  
Near Surface ◽  
Tropical Precipitation ◽  
Humidity Change ◽  
Cmip5 Gcms

A compositing scheme that predicts changes in tropical precipitation under climate change from changes in near-surface relative humidity (RH) and temperature is presented. As shown by earlier work, regions of high tropical precipitation in general circulation models (GCMs) are associated with high near-surface RH and temperature. Under climate change, it is found that high precipitation continues to be associated with the highest surface RH and temperatures in most CMIP5 GCMs, meaning that it is the “rank” of a given GCM grid box with respect to others that determines how much precipitation falls rather than the absolute value of surface temperature or RH change, consistent with the weak temperature gradient approximation. Further, it is demonstrated that the majority of CMIP5 GCMs are close to a threshold near which reductions in land RH produce large reductions in the RH ranking of some land regions, causing reductions in precipitation over land, particularly South America, and compensating increases over ocean. Recent work on predicting future changes in specific humidity allows the prediction of the qualitative sense of precipitation change in some GCMs when land surface humidity changes are unknown. However, the magnitudes of predicted changes are too small. Further study, perhaps into the role of radiative and land–atmosphere feedbacks, is necessary.

scholarly journals Intercomparison of Near-Surface Temperature and Precipitation Extremes in AMIP-2 Simulations, Reanalyses, and Observations

2005 ◽  
Vol 18 (24) ◽  
pp. 5201-5223 ◽  
Author(s):  
Viatcheslav V. Kharin ◽  
Francis W. Zwiers ◽  
Xuebin Zhang
Keyword(s):  
Surface Temperature ◽  
General Circulation ◽  
Freezing Point ◽  
Deep Convection ◽  
General Circulation Models ◽  
Atmospheric Model ◽  
Rain Gauge ◽  
Precipitation Extremes ◽  
Second Phase ◽  
Near Surface

Abstract The extremes of near-surface temperature and 24-h and 5-day mean precipitation rates are examined in simulations performed with atmospheric general circulation models (AGCMs) participating in the second phase of the Atmospheric Model Intercomparison Project (AMIP-2). The extremes are evaluated in terms of 20-yr return values of annual extremes. The model results are validated against the European Centre for Medium-Range Weather Forecasts and National Centers for Environmental Prediction reanalyses and station data. Precipitation extremes are also validated against the pentad dataset of the Global Precipitation Climatology Project, which is a blend of rain gauge observations, satellite data, and model output. On the whole, the AGCMs appear to simulate temperature extremes reasonably well. Model disagreements are larger for cold extremes than for warm extremes, particularly in wet and cloudy regions, and over sea ice and snow-covered areas. Many models exhibit an exaggerated clustering behavior for temperatures near the freezing point of water. Precipitation extremes are less reliably reproduced by the models and reanalyses. The largest disagreements are found in the Tropics where the parameterizations of deep convection affect the simulated daily precipitation extremes.

scholarly journals The relevance of mid-Holocene Arctic warming to the future

2019 ◽  
Vol 15 (4) ◽  
pp. 1375-1394 ◽  
Author(s):  
Masakazu Yoshimori ◽  
Marina Suzuki
Keyword(s):  
Surface Temperature ◽  
General Circulation ◽  
Temperature Response ◽  
Longwave Radiation ◽  
General Circulation Models ◽  
Cross Model ◽  
Arctic Warming ◽  
Temperature Changes ◽  
The Future ◽  
Arctic Climate Change

Abstract. There remain substantial uncertainties in future projections of Arctic climate change. There is a potential to constrain these uncertainties using a combination of paleoclimate simulations and proxy data, but such a constraint must be accompanied by physical understanding on the connection between past and future simulations. Here, we examine the relevance of an Arctic warming mechanism in the mid-Holocene (MH) to the future with emphasis on process understanding. We conducted a surface energy balance analysis on 10 atmosphere and ocean general circulation models under the MH and future Representative Concentration Pathway (RCP) 4.5 scenario forcings. It is found that many of the dominant processes that amplify Arctic warming over the ocean from late autumn to early winter are common between the two periods, despite the difference in the source of the forcing (insolation vs. greenhouse gases). The positive albedo feedback in summer results in an increase in oceanic heat release in the colder season when the atmospheric stratification is strong, and an increased greenhouse effect from clouds helps amplify the warming during the season with small insolation. The seasonal progress was elucidated by the decomposition of the factors associated with sea surface temperature, ice concentration, and ice surface temperature changes. We also quantified the contribution of individual components to the inter-model variance in the surface temperature changes. The downward clear-sky longwave radiation is one of major contributors to the model spread throughout the year. Other controlling terms for the model spread vary with the season, but they are similar between the MH and the future in each season. This result suggests that the MH Arctic change may not be analogous to the future in some seasons when the temperature response differs, but it is still useful to constrain the model spread in the future Arctic projection. The cross-model correlation suggests that the feedbacks in preceding seasons should not be overlooked when determining constraints, particularly summer sea ice cover for the constraint of autumn–winter surface temperature response.

scholarly journals Analog Downscaling of Seasonal Rainfall Forecasts in the Murray Darling Basin

2013 ◽  
Vol 141 (3) ◽  
pp. 1099-1117 ◽  
Author(s):  
Andrew Charles ◽  
Bertrand Timbal ◽  
Elodie Fernandez ◽  
Harry Hendon
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Seasonal Prediction ◽  
General Circulation Models ◽  
Meridional Wind ◽  
Seasonal Forecasts ◽  
Local Climate ◽  
Continental Scale ◽  
Predictive Skill ◽  
Murray Darling Basin

Abstract Seasonal predictions based on coupled atmosphere–ocean general circulation models (GCMs) provide useful predictions of large-scale circulation but lack the conditioning on topography required for locally relevant prediction. In this study a statistical downscaling model based on meteorological analogs was applied to continental-scale GCM-based seasonal forecasts and high quality historical site observations to generate a set of downscaled precipitation hindcasts at 160 sites in the South Murray Darling Basin region of Australia. Large-scale fields from the Predictive Ocean–Atmosphere Model for Australia (POAMA) 1.5b GCM-based seasonal prediction system are used for analog selection. Correlation analysis indicates modest levels of predictability in the target region for the selected predictor fields. A single best-match analog was found using model sea level pressure, meridional wind, and rainfall fields, with the procedure applied to 3-month-long reforecasts, initialized on the first day of each month from 1980 to 2006, for each model day of 10 ensemble members. Assessment of the total accumulated rainfall and number of rainy days in the 3-month reforecasts shows that the downscaling procedure corrects the local climate variability with no mean effect on predictive skill, resulting in a smaller magnitude error. The amount of total rainfall and number of rain days in the downscaled output is significantly improved over the direct GCM output as measured by the difference in median and tercile thresholds between station observations and downscaled rainfall. Confidence in the downscaled output is enhanced by strong consistency between the large-scale mean of the downscaled and direct GCM precipitation.

scholarly journals Assessing bias corrections of oceanic surface conditions for atmospheric models

2019 ◽  
Vol 12 (1) ◽  
pp. 321-342 ◽  
Author(s):  
Julien Beaumet ◽  
Gerhard Krinner ◽  
Michel Déqué ◽  
Rein Haarsma ◽  
Laurent Li
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
General Circulation ◽  
General Circulation Models ◽  
Substantial Improvement ◽  
Sea Surface ◽  
Sea Ice Concentration ◽  
Ice Concentration ◽  
Analogue Method

Abstract. Future sea surface temperature and sea-ice concentration from coupled ocean–atmosphere general circulation models such as those from the CMIP5 experiment are often used as boundary forcings for the downscaling of future climate experiments. Yet, these models show some considerable biases when compared to the observations over present climate. In this paper, existing methods such as an absolute anomaly method and a quantile–quantile method for sea surface temperature (SST) as well as a look-up table and a relative anomaly method for sea-ice concentration (SIC) are presented. For SIC, we also propose a new analogue method. Each method is objectively evaluated with a perfect model test using CMIP5 model experiments and some real-case applications using observations. We find that with respect to other previously existing methods, the analogue method is a substantial improvement for the bias correction of future SIC. Consistency between the constructed SST and SIC fields is an important constraint to consider, as is consistency between the prescribed sea-ice concentration and thickness; we show that the latter can be ensured by using a simple parameterisation of sea-ice thickness as a function of instantaneous and annual minimum SIC.

scholarly journals On the role of Eurasian autumn snow cover in dynamical seasonal predictions 

2021 ◽  
Author(s):  
Paolo Ruggieri ◽  
Marianna Benassi ◽  
Stefano Materia ◽  
Daniele Peano ◽  
Constantin Ardilouze ◽  
...  
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Land Surface ◽  
General Circulation ◽  
Dominant Role ◽  
General Circulation Models ◽  
The Arctic ◽  
Seasonal Forecasts ◽  
Eurasian Snow

<p>Seasonal climate predictions leverage on many predictable or persistent components of the Earth system that can modify the state of the atmosphere and of relant weather related variable such as temprature and precipitation. With a dominant role of the ocean, the land surface provides predictability through various mechanisms, including snow cover, with particular reference to Autumn snow cover over the Eurasian continent. The snow cover alters the energy exchange between land surface and atmosphere and induces a diabatic cooling that in turn can affect the atmosphere both locally and remotely. Lagged relationships between snow cover in Eurasia and atmospheric modes of variability in the Northern Hemisphere have been investigated and documented but are deemed to be non-stationary and climate models typically do not reproduce observed relationships with consensus. The role of Autumn Eurasian snow in recent dynamical seasonal forecasts is therefore unclear. In this study we assess the role of Eurasian snow cover in a set of 5 operational seasonal forecast system characterized by a large ensemble size and a high atmospheric and oceanic resolution. Results are compemented with a set of targeted idealised simulations with atmospheric general circulation models forced by different snow cover conditions. Forecast systems reproduce realistically regional changes of the surface energy balance associated with snow cover variability. Retrospective forecasts and idealised sensitivity experiments converge in identifying a coherent change of the circulation in the Northern Hemisphere. This is compatible with a lagged but fast feedback from the snow to the Arctic Oscillation trough a tropospheric pathway.</p>

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