scholarly journals Representation by two climate models of the dynamical and diabatic processes involved in the development of an explosively deepening cyclone during NAWDEX

2021 ◽  
Vol 2 (1) ◽  
pp. 233-253
Author(s):  
David L. A. Flack ◽  
Gwendal Rivière ◽  
Ionela Musat ◽  
Romain Roehrig ◽  
Sandrine Bony ◽  
...  
Keyword(s):  
Diabatic Heating ◽  
Climate Models ◽  
Global Climate ◽  
Weather Forecast ◽  
Relative Vorticity ◽  
Global Climate Models ◽  
Mature Stage ◽  
The North ◽  
Upper Level ◽  
Ice Water

Abstract. The dynamical and microphysical properties of a well-observed cyclone from the North Atlantic Waveguide and Downstream Impact Experiment (NAWDEX), called the Stalactite cyclone and corresponding to intensive observation period 6, is examined using two atmospheric components (ARPEGE-Climat 6.3 and LMDZ6A) of the global climate models CNRM-CM6-1 and IPSL-CM6A, respectively. The hindcasts are performed in “weather forecast mode”, run at approximately 150–200 km (low resolution, LR) and approximately 50 km (high resolution, HR) grid spacings, and initialised during the initiation stage of the cyclone. Cyclogenesis results from the merging of two relative vorticity maxima at low levels: one associated with a diabatic Rossby vortex (DRV) and the other initiated by baroclinic interaction with a pre-existing upper-level potential vorticity (PV) cut-off. All hindcasts produce (to some extent) a DRV. However, the second vorticity maximum is almost absent in LR hindcasts because of an underestimated upper-level PV cut-off. The evolution of the cyclone is examined via the quasi-geostrophic ω equation which separates the diabatic heating component from the dynamical one. In contrast to some previous studies, there is no change in the relative importance of diabatic heating with increased resolution. The analysis shows that LMDZ6A produces stronger diabatic heating compared to ARPEGE-Climat 6.3. Hindcasts initialised during the mature stage of the cyclone are compared with airborne remote-sensing measurements. There is an underestimation of the ice water content in the model compared to the one retrieved from radar-lidar measurements. Consistent with the increased heating rate in LMDZ6A compared to ARPEGE-Climat 6.3, the sum of liquid and ice water contents is higher in LMDZ6A than ARPEGE-Climat 6.3 and, in that sense, LMDZ6A is closer to the observations. However, LMDZ6A strongly overestimates the fraction of super-cooled liquid compared to the observations by a factor of approximately 50.

scholarly journals How Well do Models Represent the Development of Extra-Tropical Cyclones? Evaluation of Two General Circulation Models Against NAWDEX IOP 6 Observations

2020 ◽  
Author(s):  
David L. A. Flack ◽  
Gwendal Rivière ◽  
Ionela Musat ◽  
Romain Roehrig ◽  
Sandrine Bony ◽  
...  
Keyword(s):  
Water Content ◽  
General Circulation ◽  
Diabatic Heating ◽  
Weather Forecast ◽  
General Circulation Models ◽  
Liquid Water Content ◽  
Mature Stage ◽  
Global Circulation Models ◽  
Upper Level ◽  
Ice Water

Abstract. The dynamical and microphysical properties of a well-observed cyclone from the North Atlantic Waveguide and Downstream impact Experiment (NAWDEX), called the Stalactite cyclone and corresponding to Intensive Observation Period 6, is examined using two atmospheric global circulation models: CNRM-CM6-1 and IPSL-CM6A. The hindcasts are performed in weather forecast mode, run at CMIP~6 resolution (LR) and c.~0.5° (HR) and initialized during the initiation stage of the cyclone. Cyclogenesis results from the merging of two relative vorticity maxima at low levels: one is associated with a Diabatic Rossby Vortex (DRV) propagating from the subtropics and the other is initiated by baroclinic development and interaction with a pre-existing upper-level PV cut-off. All hindcasts produce (to some extent) a DRV. However, the second vorticity maximum is almost absent in LR hindcasts because of an underestimated upper-level PV cut-off. The evolution of the cyclone is examined via the quasi-geostrophic ω equation, which separates the diabatic heating component from the dynamical one at each given time. In contrast with some previous studies, there is no change in the relative importance of diabatic heating with increased resolution. The analysis also shows that IPSL-CM6A produces a more active cyclone compared to the CNRM-CM6-1 due to stronger diabatism. To examine this further, hindcasts initialized during the mature stage of the cyclone are compared with airborne remote-sensing measurements. There is generally an underestimation of the ice water content in the model compared to the one retrieved from radar-lidar measurements, even when the liquid water content is added. Consistent with the increased diabatism in IPSL-CM6A compared to CNRM-CM6-1, the sum of liquid and ice water contents is higher in IPSL-CM6A than CNRM-CM6-1 and, in that sense, IPSL-CM6A is closer to the observations. However, ISPL-CM6A strongly overestimates the fraction of super-cooled liquid compared to the observations by a factor of approximately 50.

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

2019 ◽  
Vol 32 (19) ◽  
pp. 6467-6490 ◽  
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.

scholarly journals Ensemble models on palaeoclimate to predict India's groundwater challenge

2013 ◽  
Vol 2 (3) ◽  
Author(s):  
Partha Sarathi Datta
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Humid Climate ◽  
Ensemble Models ◽  
North West ◽  
The Past ◽  
The North ◽  
14C Age

In many parts of the world, freshwater crisis is largely due to increasing water consumption and pollution by rapidly growing population and aspirations for economic development, but, ascribed usually to the climate. However, limited understanding and knowledge gaps in the factors controlling climate and uncertainties in the climate models are unable to assess the probable impacts on water availability in tropical regions. In this context, review of ensemble models on δ18O and δD in rainfall and groundwater, 3H- and 14C- ages of groundwater and 14C- age of lakes sediments helped to reconstruct palaeoclimate and long-term recharge in the North-west India; and predict future groundwater challenge. The annual mean temperature trend indicates both warming/cooling in different parts of India in the past and during 1901–2010. Neither the GCMs (Global Climate Models) nor the observational record indicates any significant change/increase in temperature and rainfall over the last century, and climate change during the last 1200 yrs BP. In much of the North-West region, deep groundwater renewal occurred from past humid climate, and shallow groundwater renewal from limited modern recharge over the past decades. To make water management to be more responsive to climate change, the gaps in the science of climate change need to be bridged.

IMPROVING THE NORTH AMERICAN MULTI-MODEL ENSEMBLE (NMME) PRECIPITATION FORECASTS AT SEASONAL SCALE OVER THE HIMALAYAN REGION USING MACHINE LEARNING

2021 ◽  
Author(s):  
SOURABH SHRIVASTAVA ◽  
RAM AVTAR ◽  
PRASANTA KUMAR BAL
Keyword(s):  
Machine Learning ◽  
North American ◽  
Climate Models ◽  
Global Climate ◽  
Horizontal Resolution ◽  
Summer Monsoon Rainfall ◽  
Global Climate Models ◽  
Himalayan Region ◽  
Model Ensemble ◽  
The North

The coarse horizontal resolution global climate models (GCMs) have limitations in producing large biases over the mountainous region. Also, single model output or simple multi-model ensemble (SMME) outputs are associated with large biases. While predicting the rainfall extreme events, this study attempts to use an alternative modeling approach by using five different machine learning (ML) algorithms to improve the skill of North American Multi-Model Ensemble (NMME) GCMs during Indian summer monsoon rainfall from 1982 to 2009 by reducing the model biases. Random forest (RF), AdaBoost (Ada), gradient (Grad) boosting, bagging (Bag) and extra (Extra) trees regression models are used and the results from each models are compared against the observations. In simple MME (SMME), a wet bias of 20[Formula: see text]mm/day and an RMSE up to 15[Formula: see text]mm/day are found over the Himalayan region. However, all the ML models can bring down the mean bias up to [Formula: see text][Formula: see text]mm/day and RMSE up to 2[Formula: see text]mm/day. The interannual variability in ML outputs is closer to observation than the SMME. Also, a high correlation from 0.5 to 0.8 is found between in all ML models and then in SMME. Moreover, representation of RF and Grad is found to be best out of all five ML models that represent a high correlation over the Himalayan region. In conclusion, by taking full advantage of different models, the proposed ML-based multi-model ensemble method is shown to be accurate and effective.

scholarly journals Understanding Intermodel Variability in Future Projections of a Sahelian Storm Proxy and Southern Saharan Warming

2021 ◽  
Vol 34 (2) ◽  
pp. 509-525
Author(s):  
David P. Rowell ◽  
Rory G. J. Fitzpatrick ◽  
Lawrence S. Jackson ◽  
Grace Redmond
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Global Climate ◽  
Vertical Wind Shear ◽  
Global Climate Models ◽  
Tropospheric Temperature ◽  
Storm Activity ◽  
Convective Systems ◽  
The North ◽  
Projected Changes

AbstractProjected changes in the intensity of severe rain events over the North African Sahel—falling from large mesoscale convective systems—cannot be directly assessed from global climate models due to their inadequate resolution and parameterization of convection. Instead, the large-scale atmospheric drivers of these storms must be analyzed. Here we study changes in meridional lower-tropospheric temperature gradient across the Sahel (ΔTGrad), which affect storm development via zonal vertical wind shear and Saharan air layer characteristics. Projected changes in ΔTGrad vary substantially among models, adversely affecting planning decisions that need to be resilient to adverse risks, such as increased flooding. This study seeks to understand the causes of these projection uncertainties and finds three key drivers. The first is intermodel variability in remote warming, which has strongest impact on the eastern Sahel, decaying toward the west. Second, and most important, a warming–advection–circulation feedback in a narrow band along the southern Sahara varies in strength between models. Third, variations in southern Saharan evaporative anomalies weakly affect ΔTGrad, although for an outlier model these are sufficiently substantive to reduce warming here to below that of the global mean. Together these uncertain mechanisms lead to uncertain southern Saharan/northern Sahelian warming, causing the bulk of large intermodel variations in ΔTGrad. In the southern Sahel, a local negative feedback limits the contribution to uncertainties in ΔTGrad. This new knowledge of ΔTGrad projection uncertainties provides understanding that can be used, in combination with further research, to constrain projections of severe Sahelian storm activity.

scholarly journals A Climatological Assessment of Intense Extratropical Cyclones from the Potential Vorticity Perspective

2019 ◽  
Vol 32 (8) ◽  
pp. 2369-2380 ◽  
Author(s):  
Christian Seiler
Keyword(s):  
Potential Vorticity ◽  
Relative Frequency ◽  
Climate Models ◽  
Global Climate ◽  
Potential Temperature ◽  
Relative Vorticity ◽  
Global Climate Models ◽  
Extratropical Cyclones ◽  
Stratospheric Intrusion ◽  
The Pacific

Extratropical cyclones (ETCs) are known to intensify due to three vertically interacting positive potential vorticity perturbations that are associated with potential temperature anomalies close to the surface (θB), condensational heating in the lower-level atmosphere (qsat), and stratospheric intrusion in the upper-level atmosphere (qtr). This study presents the first climatological assessment of how much each of these three mechanisms contributes to the intensity of extreme ETCs. Using relative vorticity at 850 hPa as a measure of ETC intensity, results show that in about half of all cases the largest contributions during maximum ETC intensity are associated with qsat (53% of all ETCs), followed by qtr (36%) and θB (11%). The relative frequency of storms that are dominated by qsat is higher 1) during warmer months (61% of all ETCs during warmer months) compared to colder months (50%) and 2) in the Pacific (56% of all ETCs in the Pacific) compared to the Atlantic (46%). The relative frequency of ETCs that are dominated by θB is larger 1) during colder months (13%) compared to warmer months (3%), 2) in the Atlantic (15%) compared to the Pacific (8%), and 3) in western (11%–20%) compared to eastern ocean basins (4%–9%). These findings are based on piecewise potential vorticity inversion conducted for intense ETCs that occurred from 1980 to 2016 in the Northern Hemisphere (3273 events; top 7%). The results may serve as a baseline for evaluating ETC biases and uncertainties in global climate models.

scholarly journals Mean and extreme precipitation over European river basins better simulated in a 25 km AGCM

2018 ◽  
Vol 22 (7) ◽  
pp. 3933-3950 ◽  
Author(s):  
Reinhard Schiemann ◽  
Pier Luigi Vidale ◽  
Len C. Shaffrey ◽  
Stephanie J. Johnson ◽  
Malcolm J. Roberts ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Climate Models ◽  
Global Climate ◽  
River Basins ◽  
Global Climate Models ◽  
Sensitivity Experiment ◽  
Scale Parameters ◽  
The North ◽  
Resolution Model ◽  
High Resolution Model

Abstract. Limited spatial resolution is one of the factors that may hamper applications of global climate models (GCMs), in particular over Europe with its complex coastline and orography. In this study, the representation of European mean and extreme precipitation is evaluated in simulations with an atmospheric GCM (AGCM) at different resolutions between about 135 and 25 km grid spacing in the mid-latitudes. The continent-wide root-mean-square error in mean precipitation in the 25 km model is about 25  % smaller than in the 135 km model in winter. Clear improvements are also seen in autumn and spring, whereas the model's sensitivity to resolution is very small in summer. Extreme precipitation is evaluated by estimating generalised extreme value distributions (GEVs) of daily precipitation aggregated over river basins whose surface area is greater than 50 000 km2. GEV location and scale parameters are measures of the typical magnitude and of the interannual variability of extremes, respectively. Median model biases in both these parameters are around 10 % in summer and around 20 % in the other seasons. For some river basins, however, these biases can be much larger and take values between 50 % and 100 %. Extreme precipitation is better simulated in the 25 km model, especially during autumn when the median GEV parameter biases are more than halved, and in the North European Plains, from the Loire in the west to the Vistula in the east. A sensitivity experiment is conducted showing that these resolution sensitivities in both mean and extreme precipitation are in many areas primarily due to the increase in resolution of the model orography. The findings of this study illustrate the improved capability of a global high-resolution model in simulating European mean and extreme precipitation.

Regionally Varying Assessments of Upper-Level Tropical Width in Reanalyses and CMIP5 Models Using a Tropopause Break Metric

2020 ◽  
Vol 33 (14) ◽  
pp. 5885-5903 ◽  
Author(s):  
Elinor R. Martin ◽  
Cameron R. Homeyer ◽  
Roarke A. McKinzie ◽  
Kevin M. McCarthy ◽  
Tao Xian
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Models ◽  
Cmip5 Models ◽  
The Past ◽  
East Pacific ◽  
Change Climate ◽  
Upper Level ◽  
The Tropics

AbstractChanges in tropical width can have important consequences in sectors including ecosystems, agriculture, and health. Observations suggest tropical expansion over the past 30 years although studies have not agreed on the magnitude of this change. Climate model projections have also indicated an expansion and show similar uncertainty in its magnitude. This study utilizes an objective, longitudinally varying, tropopause break method to define the extent of the tropics at upper levels. The location of the tropopause break is associated with enhanced stratosphere–troposphere exchange and thus its structure influences the chemical composition of the stratosphere. The method shows regional variations in the width of the upper-level tropics in the past and future. Four modern reanalyses show significant contraction of the tropics over the eastern Pacific between 1981 and 2015, and slight but significant expansion in other regions. The east Pacific narrowing contributes to zonal mean narrowing, contradicting prior work, and is attributed to the use of monthly and zonal mean data in prior studies. Six global climate models perform well in representing the climatological location of the tropical boundary. Future projections show a spread in the width trend (from ~0.5° decade−1 of narrowing to ~0.4° decade−1 of widening), with a narrowing projected across the east Pacific and Northern Hemisphere Americas. This study illustrates that this objective tropopause break method that uses instantaneous data and does not require zonal averaging is appropriate for identifying upper-level tropical width trends and the break location is connected with local and regional changes in precipitation.

scholarly journals Sensitivity of Limiting Hurricane Intensity to SST in the Atlantic from Observations and GCMs

2013 ◽  
Vol 26 (16) ◽  
pp. 5949-5957 ◽  
Author(s):  
James B. Elsner ◽  
Sarah E. Strazzo ◽  
Thomas H. Jagger ◽  
Timothy LaRow ◽  
Ming Zhao
Keyword(s):  
Climate Models ◽  
North Atlantic Ocean ◽  
Global Climate ◽  
Atmospheric Model ◽  
Global Climate Models ◽  
Lower Sensitivity ◽  
Hurricane Intensity ◽  
University Center ◽  
The North ◽  
Low Sensitivity

Abstract A statistical model for the intensity of the strongest hurricanes has been developed and a new methodology introduced for estimating the sensitivity of the strongest hurricanes to changes in sea surface temperature. Here, the authors use this methodology on observed hurricanes and hurricanes generated from two global climate models (GCMs). Hurricanes over the North Atlantic Ocean during the period 1981–2010 show a sensitivity of 7.9 ± 1.19 m s−1 K−1 (standard error; SE) when over seas warmer than 25°C. In contrast, hurricanes over the same region and period generated from the GFDL High Resolution Atmospheric Model (HiRAM) show a significantly lower sensitivity with the highest at 1.8 ± 0.42 m s−1 K−1 (SE). Similar weaker sensitivity is found using hurricanes generated from the Florida State University Center for Ocean–Atmospheric Prediction Studies (FSU-COAPS) model with the highest at 2.9 ± 2.64 m s−1 K−1 (SE). A statistical refinement of HiRAM-generated hurricane intensities heightens the sensitivity to a maximum of 6.9 ± 3.33 m s−1 K−1 (SE), but the increase is offset by additional uncertainty associated with the refinement. Results suggest that the caution that should be exercised when interpreting GCM scenarios of future hurricane intensity stems from the low sensitivity of limiting GCM-generated hurricane intensity to ocean temperature.

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