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 A prognostic pollen emissions model for climate models (PECM1.0)

2017 ◽  
Author(s):  
Matthew C. Wozniak ◽  
Allison Steiner
Keyword(s):  
United States ◽  
Land Cover ◽  
Climate Models ◽  
Climate Model ◽  
Vegetation Type ◽  
Global Climate ◽  
The United States ◽  
Global Climate Models ◽  
Pollen Counts ◽  
Surface Pollen

Abstract. We develop a prognostic model of Pollen Emissions for Climate Models (PECM) for use within regional and global climate models to simulate pollen counts over the seasonal cycle based on geography, vegetation type and meteorological parameters. Using modern surface pollen count data, empirical relationships between prior-year annual average temperature and pollen season start dates and end dates are developed for deciduous broadleaf trees (Acer, Alnus, Betula, Fraxinus, Morus, Platanus, Populus, Quercus, Ulmus), evergreen needleleaf trees (Cupressaceae, Pinaceae), grasses (Poaceae; C3, C4), and ragweed (Ambrosia). This regression model explains as much as 57 % of the variance in pollen phenological dates, and it is used to create a climate-flexible phenology that can be used to study the response of wind-driven pollen emissions to climate change. The emissions model is evaluated in a regional climate model (RegCM4) over the continental United States by prescribing an emission potential from PECM and transporting pollen as aerosol tracers. We evaluate two different pollen emissions scenarios in the model: (1) using a taxa-specific land cover database, phenology and emission potential, and (2) a PFT-based land cover, phenology and emission potential. The resulting surface concentrations for both simulations are evaluated against observed surface pollen counts in five climatic subregions. Given prescribed pollen emissions, the RegCM4 simulates observed concentrations within an order of magnitude, although the performance of the simulations in any subregion is strongly related to the land cover representation and the number of observation sites used to create the empirical phenological relationship. The taxa-based model provides a better representation of the phenology of tree-based pollen counts than the PFT-based model, however we note that the PFT-based version provides a useful and climate-flexible emissions model for the general representation of the pollen phenology over the United States.

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 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’.

Extreme Events in High Resolution CMCC Regional and Global Climate Models

2011 ◽  
Author(s):  
Enrico Scoccimarro ◽  
Silvio Gualdi ◽  
Antonella Sanna ◽  
Edoardo Bucchignani ◽  
Myriam Montesarchio
Keyword(s):  
High Resolution ◽  
Extreme Events ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models

The MJO-QBO Relationship in a GCM with Stratospheric Nudging

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.

scholarly journals An evaluation of the importance of spatial resolution in a global climate and hydrological model based on the Rhine and Mississippi basin

2017 ◽  
Author(s):  
Imme Benedict ◽  
Chiel C. van Heerwaarden ◽  
Albrecht H. Weerts ◽  
Wilco Hazeleger
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Large Scale ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Global Scale ◽  
Global Climate Models ◽  
Convective Processes ◽  
Parameter Values

Abstract. The hydrological cycle of river basins can be simulated by combining global climate models (GCMs) and global hydrological models (GHMs). The spatial resolution of these models is restricted by computational resources and therefore limits the processes and level of detail that can be resolved. To further improve simulations of precipitation and river-runoff on a global scale, we assess and compare the benefits of an increased resolution for a GCM and a GHM. We focus on the Rhine and Mississippi basin. Increasing the resolution of a GCM (1.125° to 0.25°) results in more realistic large-scale circulation patterns over the Rhine and an improved precipitation budget. These improvements with increased resolution are not found for the Mississippi basin, most likely because precipitation is strongly dependent on the representation of still unresolved convective processes. Increasing the resolution of vegetation and orography in the high resolution GHM (from 0.5° to 0.05°) shows no significant differences in discharge for both basins, because the hydrological processes depend highly on other parameter values that are not readily available at high resolution. Therefore, increasing the resolution of the GCM provides the most straightforward route to better results. This route works best for basins driven by large-scale precipitation, such as the Rhine basin. For basins driven by convective processes, such as the Mississippi basin, improvements are expected with even higher resolution convection permitting models.

scholarly journals Climate change will increase potential hydropower production in six Arctic Council member countries based on probabilistic hydrological projections

2018 ◽  
Author(s):  
Elena Shevnina ◽  
Karoliina Pilli-Sihvola ◽  
Riina Haavisto ◽  
Timo Vihma ◽  
Andrey Silaev
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
The United States ◽  
Annual Runoff ◽  
Global Climate Models ◽  
Exceedance Probability ◽  
Arctic Council ◽  
Pearson Type ◽  
Hydropower Production ◽  
Runoff Rate

Abstract. Potential hydropower production for 2020–2050 is calculated for 173 catchments located over the territories of Finland, Sweden, Norway, the Russian Federation, Canada and the United States. The results are based on hydrological river runoff projections assessed together with their exceedance probabilities. The annual runoff rate of particular exceedance probability was modelled with the Pearson type 3 distribution from three parameters (mean values, coefficient of variation and coefficient of skewness) simulated by the probabilistic hydrological MARcov Chain System (MARCS) model. The probabilistic projections of annual runoff were simulated from outputs of four global climate models under three Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5). The future potential hydropower production was evaluated based on annual runoff of low and high exceedance probabilities, and then aggregated at a country level. Under forcing from climate models that project a large increase in precipitation (CaEMS2 and MPI-EMS-LM), the expected potential hydropower production in the six countries increased by 14.0 to 18.0 % according to the projected values of annual runoff rate on exceedance probabilities of 10 and 90 %. This increase in water resources allows for 10–15 % more hydropower energy generation by rivers located in Russia, Finland, Norway, and Sweden. For the USA and Canada, the potential hydropower production is projected to increases by 4.0–9.0 %. Under forcing from climate models that project a smaller increase in precipitation (HadGEM2-ES and INMCM4), the increase of potential hydropower production by 2050 was predicted to be 2.1–8.4 % over the six countries considered.

scholarly journals Assessing the impact of global warming on worldwide open field tomato cultivation through CSIRO-Mk3·0 global climate model

2016 ◽  
Vol 155 (3) ◽  
pp. 407-420 ◽  
Author(s):  
R. S. SILVA ◽  
L. KUMAR ◽  
F. SHABANI ◽  
M. C. PICANÇO
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Open Field ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Current Model ◽  
Global Climate Models ◽  
The Impact

SUMMARYTomato (Solanum lycopersicum L.) is one of the most important vegetable crops globally and an important agricultural sector for generating employment. Open field cultivation of tomatoes exposes the crop to climatic conditions, whereas greenhouse production is protected. Hence, global warming will have a greater impact on open field cultivation of tomatoes rather than the controlled greenhouse environment. Although the scale of potential impacts is uncertain, there are techniques that can be implemented to predict these impacts. Global climate models (GCMs) are useful tools for the analysis of possible impacts on a species. The current study aims to determine the impacts of climate change and the major factors of abiotic stress that limit the open field cultivation of tomatoes in both the present and future, based on predicted global climate change using CLIMatic indEX and the A2 emissions scenario, together with the GCM Commonwealth Scientific and Industrial Research Organisation (CSIRO)-Mk3·0 (CS), for the years 2050 and 2100. The results indicate that large areas that currently have an optimum climate will become climatically marginal or unsuitable for open field cultivation of tomatoes due to progressively increasing heat and dry stress in the future. Conversely, large areas now marginal and unsuitable for open field cultivation of tomatoes will become suitable or optimal due to a decrease in cold stress. The current model may be useful for plant geneticists and horticulturalists who could develop new regional stress-resilient tomato cultivars based on needs related to these modelling projections.

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