Using PRIMAVERA high-resolution global climate models for European windstorm risk assessment in present and future climates for the (re)insurance industry

2020 ◽  
Author(s):  
Julia Lockwood ◽  
Erika Palin ◽  
Galina Guentchev ◽  
Malcolm Roberts
Keyword(s):  
High Resolution ◽  
Climate Models ◽  
Climate Model ◽  
Insurance Industry ◽  
Global Climate ◽  
Storm Track ◽  
Global Climate Models ◽  
Climate Modelling ◽  
Business And Society ◽  
High Resolution Models

<p>PRIMAVERA is a European Union Horizon2020 project about creating a new generation of advanced and well-evaluated high-resolution global climate models, for the benefit of governments, business and society in general. The project has been engaging with several sectors, including finance, transport, and energy, to understand the extent to which any improved process understanding arising from high-resolution global climate modelling can – in turn – help with using climate model output to address user needs.</p><p>In this talk we will outline our work for the finance and (re)insurance industries.  Following consultation with members of the industry, we are using PRIMAVERA climate models to generate a European windstorm event set for use in catastrophe modelling and risk analysis.  The event set is generated from five different climate models, each run at a selection of resolutions ranging from 18-140km, covering the period 1950-2050, giving approximately 1700 years of climate model data in total.  High-resolution climate models tend to have reduced biases in storm track position (which is too zonal in low-resolution climate models) and windstorm intensity.  We will compare the properties of the windstorm footprints and associated risk across the different models and resolutions, to assess whether the high-resolution models lead to improved estimation of European windstorm risk.  We will also compare windstorm risk in present and future climates, to see if a consistent picture emerges between models.  Finally we will address the question of whether the event sets from each PRIMAVERA model can be combined to form a multi-model event set ensemble covering thousands of years of windstorm data.</p>

scholarly journals Effects of Convective Gravity Wave Drag in the Southern Hemisphere Winter Stratosphere

2013 ◽  
Vol 70 (7) ◽  
pp. 2120-2136 ◽  
Author(s):  
Hyun-Joo Choi ◽  
Hye-Yeong Chun
Keyword(s):  
Gravity Wave ◽  
Southern Hemisphere ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Storm Track ◽  
Wave Drag ◽  
Global Climate Models ◽  
Systematic Biases ◽  
Hemisphere Winter

Abstract The excessively strong polar jet and cold pole in the Southern Hemisphere winter stratosphere are systematic biases in most global climate models and are related to underestimated wave drag in the winter extratropical stratosphere—namely, missing gravity wave drag (GWD). Cumulus convection is strong in the winter extratropics in association with storm-track regions; thus, convective GWD could be one of the missing GWDs in models that do not adopt source-based nonorographic GWD parameterizations. In this study, the authors use the Whole Atmosphere Community Climate Model (WACCM) and show that the zonal-mean wind and temperature biases in the Southern Hemisphere winter stratosphere of the model are significantly alleviated by including convective GWD (GWDC) parameterizations. The reduction in the wind biases is due to enhanced wave drag in the winter extratropical stratosphere, which is caused directly by the additional GWDC and indirectly by the increased existing nonorographic GWD and resolved wave drag in response to the GWDC. The cold temperature biases are alleviated by increased downwelling in the winter polar stratosphere, which stems from an increased poleward motion due to enhanced wave drag in the winter extratropical stratosphere. A comparison between two simulations separately using the ray-based and columnar GWDC parameterizations shows that the polar night jet with a ray-based GWDC parameterization is much more realistic than that with a columnar GWDC parameterization.

scholarly journals Characterisation of the Antarctic stratospheric vortex mixing barrier

2021 ◽  
Author(s):  
◽  
Christopher Cameron
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Effective Diffusivity ◽  
Global Climate Models ◽  
Model Representation ◽  
Climate Modelling ◽  
Air Masses ◽  
The Face ◽  
The Antarctic

<p>The strongest stratospheric circulation in the Southern Hemisphere is the Antarctic Circumpolar Vortex (ACV) which forms each winter and spring as a zone of westerly winds surrounding Antarctica, presenting a barrier to transport of air masses between middle and high-latitudes. This barrier contributes to stratospheric temperatures above the polar region dropping sufficiently low in spring to allow for the processes leading to ozone destruction. Unfortunately, the ACV is generally not well simulated in Global Climate Models (GCMs), and this presents a challenge for model accuracy and projections in the face of a changing climate and a recovering ozone hole.  In this research, an assessment is made of the performance of a range of mixing metrics in representing the ACV based on reanalyses, including: Effective Diffusivity, Contour Crossing, the Lagrangian function $M$, and Meridional Impermeability. It is shown that Meridional Impermeability -- which provides a measure of the strength of the meridional mixing barrier as a function of potential vorticity (PV) gradient and wind-speed -- acts as a useful proxy for more complex metrics. In addition, Meridional Impermeability displays a well-defined vortex profile across equivalent latitude, which is not seen to the same degree in the other metrics assessed.  Representation of the ACV is further compared between climate models and reanalyses based on Meridional Impermeability. It is shown that while climate models have improved in their representation of the vortex barrier over time, there are still significant discrepancies between models and reanalyses. One cause of these discrepancies may result from the use of prescribed ozone fields rather than interactive ozone chemistry. This is further examined by comparing Chemistry Climate Model (CCM) simulations using interactive ozone chemistry, with those using prescribed ozone at either 3-D (i.e., height, latitude and longitude) or 2-D (i.e., height, latitude) dimensionality.   Considerable improvement in the representation of the ACV can be achieved by shifting from 2-D to 3-D prescribed ozone fields, and interactive ozone chemistry further improves its representation. However, discrepancies in model representation of the ACV still remain. Previous researchers have also attributed discrepancies in model representation of the polar vortices to the model resolution, and the parameterization of gravity waves at the sub-grid scale -- these factors are considered to contribute to the discrepancies found in simulations undertaken here also.   The results of this research are expected to provide guidance to improve the representation of vortex processes in climate modelling.</p>

scholarly journals Comparison of Statistical and Dynamic Downscaling Techniques in Generating High-Resolution Temperatures in China from CMIP5 GCMs

2020 ◽  
Vol 59 (2) ◽  
pp. 207-235 ◽  
Author(s):  
Lei Zhang ◽  
YinLong Xu ◽  
ChunChun Meng ◽  
XinHua Li ◽  
Huan Liu ◽  
...  
Keyword(s):  
High Resolution ◽  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Global Climate Models ◽  
Maximum Temperature ◽  
The Tibetan Plateau ◽  
Dynamic Downscaling

AbstractIn aiming for better access to climate change information and for providing climate service, it is important to obtain reliable high-resolution temperature simulations. Systematic comparisons are still deficient between statistical and dynamic downscaling techniques because of their inherent unavoidable uncertainties. In this paper, 20 global climate models (GCMs) and one regional climate model [Providing Regional Climates to Impact Studies (PRECIS)] are employed to evaluate their capabilities in reproducing average trends of mean temperature (Tm), maximum temperature (Tmax), minimum temperature (Tmin), diurnal temperature range (DTR), and extreme events represented by frost days (FD) and heat-wave days (HD) across China. It is shown generally that bias of temperatures from GCMs relative to observations is over ±1°C across more than one-half of mainland China. PRECIS demonstrates better representation of temperatures (except for HD) relative to GCMs. There is relatively better performance in Huanghuai, Jianghuai, Jianghan, south Yangzi River, and South China, whereas estimation is not as good in Xinjiang, the eastern part of northwest China, and the Tibetan Plateau. Bias-correction spatial disaggregation is used to downscale GCMs outputs, and bias correction is applied for PRECIS outputs, which demonstrate better improvement to a bias within ±0.2°C for Tm, Tmax, Tmin, and DTR and ±2 days for FD and HD. Furthermore, such improvement is also verified by the evidence of increased spatial correlation coefficient and symmetrical uncertainty, decreased root-mean-square error, and lower standard deviation for reproductions. It is seen from comprehensive ranking metrics that different downscaled models show the most improvement across different climatic regions, implying that optional ensembles of models should be adopted to provide sufficient high-quality climate information.

scholarly journals Blue Water in Europe: Estimates of Current and Future Availability and Analysis of Uncertainty

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 420 ◽  
Author(s):  
Alvaro Sordo-Ward ◽  
Isabel Granados ◽  
Ana Iglesias ◽  
Luis Garrote
Keyword(s):  
High Resolution ◽  
Water Availability ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Baseline Period ◽  
Global Climate Models ◽  
Blue Water ◽  
Large Area

This study presents a regional assessment of future blue water availability in Europe under different assumptions. The baseline period (1960 to 1999) is compared to the near future (2020 to 2059) and the long-term future (2060 to 2099). Blue water availability is estimated as the maximum amount of water supplied at a certain point of the river network that satisfies a defined demand, taking into account specified reliability requirements. Water availability is computed with the geospatial high-resolution Water Availability and Adaptation Policy Assessment (WAAPA) model. The WAAPA model definition for this study extends over 6 million km2 in Europe and considers almost 4000 sub-basins in Europe. The model takes into account 2300 reservoirs larger than 5 hm3, and the dataset of Hydro 1k with 1700 sub-basins. Hydrological scenarios for this study were taken from the Inter-Sectoral Impact Model Inter-Comparison Project and included simulations of five global climate models under different Representative Concentration Pathways scenarios. The choice of method is useful for evaluating large area regional studies that include high resolution on the systems´ characterization. The results highlight large uncertainties associated with a set of local water availability estimates across Europe. Climate model uncertainties for mean annual runoff and potential water availability were found to be higher than scenario uncertainties. Furthermore, the existing hydraulic infrastructure and its management have played an important role by decoupling water availability from hydrologic variability. This is observed for all climate models, the emissions scenarios considered, and for near and long-term future. The balance between water availability and withdrawals is threatened in some regions, such as the Mediterranean region. The results of this study contribute to defining potential challenges in water resource systems and regional risk areas.

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 Assessing climate model software quality: a defect density analysis of three models

2012 ◽  
Vol 5 (1) ◽  
pp. 347-382 ◽  
Author(s):  
J. Pipitone ◽  
S. Easterbrook
Keyword(s):  
Software Quality ◽  
Climate Models ◽  
Climate Model ◽  
Defect Density ◽  
Global Climate ◽  
Global Climate Models ◽  
Climate Modelling ◽  
Density Analysis ◽  
Bug Tracking ◽  
Software Trustworthiness

Abstract. A climate model is an executable theory of the climate; the model encapsulates climatological theories in software so that they can be simulated and their implications investigated. Thus, in order to trust a climate model one must trust that the software it is built from is built correctly. Our study explores the nature of software quality in the context of climate modelling. We performed an analysis of defect reports and defect fixes in several versions of leading global climate models by collecting defect data from bug tracking systems and version control repository comments. We found that the climate models all have very low defect densities compared to well-known, similarly sized open-source projects. We discuss the implications of our findings for the assessment of climate model software trustworthiness.

Future Changes in the Hydrologic Cycle Associated with Flood-Producing Storms in California

2020 ◽  
Vol 21 (11) ◽  
pp. 2607-2621
Author(s):  
Erin Dougherty ◽  
Erin Sherman ◽  
Kristen L. Rasmussen
Keyword(s):  
High Resolution ◽  
Water Resources ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
The United States ◽  
Global Climate Models ◽  
Cool Season ◽  
Atmospheric Rivers ◽  
Orographic Rainfall

AbstractCalifornia receives much of its precipitation from cool-season atmospheric rivers, which contribute to water resources and flooding. In winter 2017, a large number of atmospheric rivers caused anomalous winter precipitation, near-saturated soils, and a partial melting of snowpack, which led to excessive runoff that damaged the emergency spillway of the Oroville Dam. Given the positive and negative impacts ARs have in California, it is necessary to understand how they will change in a future climate. While prior studies have examined future changes in the frequency of atmospheric rivers impacting the West Coast of the United States, these studies primarily use coarse global climate models that are unable to resolve the complex terrain of this region. Such a limitation is overcome by using a high-resolution convection-permitting regional climate model, which resolves complex topography and orographic rainfall processes that are the main drivers of heavy precipitation in landfalling atmospheric rivers. This high-resolution model is used to examine changes to precipitation and runoff in California’s cool season from 2002 to 2013, particularly in flood-producing storms associated with atmospheric rivers, in a future, warmer climate using a pseudo–global warming approach. In 45 flood-producing storms, precipitation and runoff increase by 21%–26% and 15%–34%, respectively, while SWE decreases by 32%–90%, with the greatest changes at mid-elevations. These trends are consistent with future precipitation changes during the entire cool season. Results suggest more intense floods and less snowpack available for water resources in the future, which should be carefully considered in California’s future water management plans.

scholarly journals Assessing climate model software quality: a defect density analysis of three models

2012 ◽  
Vol 5 (4) ◽  
pp. 1009-1022 ◽  
Author(s):  
J. Pipitone ◽  
S. Easterbrook
Keyword(s):  
Software Quality ◽  
Climate Models ◽  
Climate Model ◽  
Defect Density ◽  
Global Climate ◽  
Global Climate Models ◽  
Climate Modelling ◽  
Density Analysis ◽  
Bug Tracking ◽  
Software Trustworthiness

Abstract. A climate model is an executable theory of the climate; the model encapsulates climatological theories in software so that they can be simulated and their implications investigated. Thus, in order to trust a climate model, one must trust that the software it is built from is built correctly. Our study explores the nature of software quality in the context of climate modelling. We performed an analysis of defect reports and defect fixes in several versions of leading global climate models by collecting defect data from bug tracking systems and version control repository comments. We found that the climate models all have very low defect densities compared to well-known, similarly sized open-source projects. We discuss the implications of our findings for the assessment of climate model software trustworthiness.

scholarly journals Characterisation of the Antarctic stratospheric vortex mixing barrier

2021 ◽  
Author(s):  
◽  
Christopher Cameron
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Effective Diffusivity ◽  
Global Climate Models ◽  
Model Representation ◽  
Climate Modelling ◽  
Air Masses ◽  
The Face ◽  
The Antarctic

<p>The strongest stratospheric circulation in the Southern Hemisphere is the Antarctic Circumpolar Vortex (ACV) which forms each winter and spring as a zone of westerly winds surrounding Antarctica, presenting a barrier to transport of air masses between middle and high-latitudes. This barrier contributes to stratospheric temperatures above the polar region dropping sufficiently low in spring to allow for the processes leading to ozone destruction. Unfortunately, the ACV is generally not well simulated in Global Climate Models (GCMs), and this presents a challenge for model accuracy and projections in the face of a changing climate and a recovering ozone hole.  In this research, an assessment is made of the performance of a range of mixing metrics in representing the ACV based on reanalyses, including: Effective Diffusivity, Contour Crossing, the Lagrangian function $M$, and Meridional Impermeability. It is shown that Meridional Impermeability -- which provides a measure of the strength of the meridional mixing barrier as a function of potential vorticity (PV) gradient and wind-speed -- acts as a useful proxy for more complex metrics. In addition, Meridional Impermeability displays a well-defined vortex profile across equivalent latitude, which is not seen to the same degree in the other metrics assessed.  Representation of the ACV is further compared between climate models and reanalyses based on Meridional Impermeability. It is shown that while climate models have improved in their representation of the vortex barrier over time, there are still significant discrepancies between models and reanalyses. One cause of these discrepancies may result from the use of prescribed ozone fields rather than interactive ozone chemistry. This is further examined by comparing Chemistry Climate Model (CCM) simulations using interactive ozone chemistry, with those using prescribed ozone at either 3-D (i.e., height, latitude and longitude) or 2-D (i.e., height, latitude) dimensionality.   Considerable improvement in the representation of the ACV can be achieved by shifting from 2-D to 3-D prescribed ozone fields, and interactive ozone chemistry further improves its representation. However, discrepancies in model representation of the ACV still remain. Previous researchers have also attributed discrepancies in model representation of the polar vortices to the model resolution, and the parameterization of gravity waves at the sub-grid scale -- these factors are considered to contribute to the discrepancies found in simulations undertaken here also.   The results of this research are expected to provide guidance to improve the representation of vortex processes in climate modelling.</p>

scholarly journals The effect of geographic sampling on evaluation of extreme precipitation in high-resolution climate models

2020 ◽  
Vol 6 (2) ◽  
pp. 115-139
Author(s):  
Mark D. Risser ◽  
Michael F. Wehner
Keyword(s):  
High Resolution ◽  
Observational Data ◽  
Climate Models ◽  
Climate Model ◽  
Horizontal Resolution ◽  
Global Climate Models ◽  
Boreal Winter ◽  
Weather Stations ◽  
High Resolution Models ◽  
The Impact

Abstract. Traditional approaches for comparing global climate models and observational data products typically fail to account for the geographic location of the underlying weather station data. For modern global high-resolution models with a horizontal resolution of tens of kilometers, this is an oversight since there are likely grid cells where the physical output of a climate model is compared with a statistically interpolated quantity instead of actual measurements of the climate system. In this paper, we quantify the impact of geographic sampling on the relative performance of high-resolution climate model representations of precipitation extremes in boreal winter (December–January–February) over the contiguous United States (CONUS), comparing model output from five early submissions to the HighResMIP subproject of the CMIP6 experiment. We find that properly accounting for the geographic sampling of weather stations can significantly change the assessment of model performance. Across the models considered, failing to account for sampling impacts the different metrics (extreme bias, spatial pattern correlation, and spatial variability) in different ways (both increasing and decreasing). We argue that the geographic sampling of weather stations should be accounted for in order to yield a more straightforward and appropriate comparison between models and observational data sets, particularly for high-resolution models with a horizontal resolution of tens of kilometers. While we focus on the CONUS in this paper, our results have important implications for other global land regions where the sampling problem is more severe.

Sign in / Sign up

Export Citation Format

Share Document