The Influence of Flow Projection Errors on Flood Hazard Estimates in Future Climate Conditions

The continuous simulation approach to assessing the impact of climate change on future flood hazards consists of a chain of consecutive actions, starting from the choice of the global climate model (GCM) driven by an assumed CO2 emission scenario, through the downscaling of climatic forcing to a catchment scale, an estimation of flow using a hydrological model, and subsequent derivation of flood hazard maps with the help of a flow routing model. The procedure has been applied to the Biala Tarnowska catchment, Southern Poland. Future climate projections of rainfall and temperature are used as inputs to the precipitation-runoff model simulating flow in part of the catchment upstream of a modeled river reach. An application of a lumped-parameter emulator instead of a distributed flow routing model, MIKE11, substantially lowers the required computation times. A comparison of maximum inundation maps derived using both the flow routing model, MIKE11, and its lump-parameter emulator shows very small differences, which supports the feasibility of the approach. The relationship derived between maximum annual inundation areas and the upstream flow of the study can be used to assess the floodplain extent response to future climate changes. The analysis shows the large influence of the one-grid-storm error in climate projections on the return period of annual maximum inundation areas and their uncertainty bounds.

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Analysis and Projection of Flood Hazards over China

Water ◽

10.3390/w11051022 ◽

2019 ◽

Vol 11 (5) ◽

pp. 1022 ◽

Cited By ~ 8

Author(s):

Yulian Liang ◽

Yongli Wang ◽

Yinjun Zhao ◽

Yuan Lu ◽

Xiaoying Liu

Keyword(s):

21St Century ◽

Flood Control ◽

Climate Model ◽

Southern China ◽

Flood Hazard ◽

Global Climate ◽

Global Climate Model ◽

Flood Hazards ◽

Rcp Scenarios ◽

Meteorological Observations

Floods have been experienced with greater frequency and more severity under global climate change. To understand the flood hazard and its variation in the future, the current and future flood hazards in the 21st century in China are discussed. Floods and their trends are assessed using the accumulation precipitation during heavy rainfall process (AP_HRP), which are calculated based on historical meteorological observations and the outputs of a global climate model (GCM) under three Representative Concentration Pathway (RCP) scenarios. The flood-causing HRPs counted by the flood-causing critical precipitation (the 60% fractile of AP_HRP) capture more than 70% of historical flood events. The projection results indicate that the flood hazards could increase under RCP4.5 and RCP8.5 and increase slightly under RCP2.6 during the 21st century (2011–2099). The spatial characteristics of flood hazards and their increasing trends under the three RCPs are similar in most areas of China. More floods could occur in southern China, including Guangdong, Hainan, Guangxi and Fujian provinces, which could become more serious in southeastern China and the northern Yunnan province. Construction of water conservancy projects, reservoir dredging, improvement of drainage and irrigation equipment and enhancement of flood control and storage capacity can mitigate the impacts of floods and waterlogging on agriculture.

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The Impact of Climate Change on Meningitis in Northwest Nigeria: An Assessment Using CMIP5 Climate Model Simulations

Weather Climate and Society ◽

10.1175/wcas-d-13-00068.1 ◽

2014 ◽

Vol 6 (3) ◽

pp. 371-379 ◽

Cited By ~ 9

Author(s):

Auwal F. Abdussalam ◽

Andrew J. Monaghan ◽

Daniel F. Steinhoff ◽

Vanja M. Dukic ◽

Mary H. Hayden ◽

...

Keyword(s):

Climate Change ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Treatment Strategies ◽

Coupled Model ◽

Annual Incidence ◽

Future Climate ◽

Future Climate Change ◽

The Impact

Abstract Meningitis remains a major health burden throughout Sahelian Africa, especially in heavily populated northwest Nigeria with an annual incidence rate ranging from 18 to 200 per 100 000 people for 2000–11. Several studies have established that cases exhibit sensitivity to intra- and interannual climate variability, peaking during the hot and dry boreal spring months, raising concern that future climate change may increase the incidence of meningitis in the region. The impact of future climate change on meningitis risk in northwest Nigeria is assessed by forcing an empirical model of meningitis with monthly simulations of seven meteorological variables from an ensemble of 13 statistically downscaled global climate model projections from phase 5 of the Coupled Model Intercomparison Experiment (CMIP5) for representative concentration pathway (RCP) 2.6, 6.0, and 8.5 scenarios, with the numbers representing the globally averaged top-of-the-atmosphere radiative imbalance (in W m−2) in 2100. The results suggest future temperature increases due to climate change have the potential to significantly increase meningitis cases in both the early (2020–35) and late (2060–75) twenty-first century, and for the seasonal onset of meningitis to begin about a month earlier on average by late century, in October rather than November. Annual incidence may increase by 47% ± 8%, 64% ± 9%, and 99% ± 12% for the RCP 2.6, 6.0, and 8.5 scenarios, respectively, in 2060–75 with respect to 1990–2005. It is noteworthy that these results represent the climatological potential for increased cases due to climate change, as it is assumed that current prevention and treatment strategies will remain similar in the future.

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Trends in projections of standardized precipitation indices in a future climate in Poland

Hydrology and Earth System Sciences ◽

10.5194/hess-20-1947-2016 ◽

2016 ◽

Vol 20 (5) ◽

pp. 1947-1969 ◽

Cited By ~ 22

Author(s):

Marzena Osuch ◽

Renata J. Romanowicz ◽

Deborah Lawrence ◽

Wai K. Wong

Keyword(s):

Bias Correction ◽

Climate Models ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Standardized Precipitation Index ◽

Future Climate ◽

Future Climate Change ◽

Climate Projections ◽

Monthly Precipitation

Abstract. Possible future climate change effects on dryness conditions in Poland are estimated for six climate projections using the standardized precipitation index (SPI). The time series of precipitation represent six different climate model runs under the selected emission scenario for the period 1971–2099. Monthly precipitation values were used to estimate the SPI for multiple timescales (1, 3, 6, 12, and 24 months) for a spatial resolution of 25 km for the whole country. Trends in the SPI were analysed using the Mann–Kendall test with Sen's slope estimator for each grid cell for each climate model projection and aggregation scale, and results obtained for uncorrected precipitation and bias corrected precipitation were compared. Bias correction was achieved using a distribution-based quantile mapping (QM) method in which the climate model precipitation series were adjusted relative to gridded precipitation data for Poland. The results show that the spatial pattern of the trend depends on the climate model, the timescale considered and on the bias correction. The effect of change on the projected trend due to bias correction is small compared to the variability among climate models. We also summarize the mechanisms underlying the influence of bias correction on trends in precipitation and the SPI using a simple example of a linear bias correction procedure. In both cases, the bias correction by QM does not change the direction of changes but can change the slope of trend, and the influence of bias correction on SPI is much reduced. We also have noticed that the results for the same global climate model, driving different regional climate model, are characterized by a similar pattern of changes, although this behaviour is not seen at all timescales and seasons.

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Revisiting the Krakatau 1883 Volcanic Aerosol Dispersal

10.5194/egusphere-egu21-10489 ◽

2021 ◽

Author(s):

Rafael Castro ◽

Tushar Mittal ◽

Stephen Self

Keyword(s):

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Volcanic Eruptions ◽

Climate Impact ◽

Volcanic Plume ◽

Quasi Biennial Oscillation ◽

Aerosol Cloud ◽

Pinatubo Eruption ◽

The Impact

The 1883 Krakatau eruption is one of the most well-known historical volcanic eruptions due to its significant global climate impact as well as first recorded observations of various aerosol associated optical and physical phenomena. Although much work has been done on the former by comparison of global climate model predictions/ simulations with instrumental and proxy climate records, the latter has surprisingly not been studied in similar detail. In particular, there is a wealth of observations of vivid red sunsets, blue suns, and other similar features, that can be used to analyze the spatio-temporal dispersal of volcanic aerosols in summer to winter 1883. Thus, aerosol cloud dispersal after the Krakatau eruption can be estimated, bolstered by aerosol cloud behavior as monitored by satellite-based instrument observations after the 1991 Pinatubo eruption. This is one of a handful of large historic eruptions where this analysis can be done (using non-climate proxy methods). In this study, we model particle trajectories of the Krakatau eruption cloud using the Hysplit trajectory model and compare our results with our compiled observational dataset (principally using Verbeek 1884, the Royal Society report, and Kiessling 1884).In particular, we explore the effect of different atmospheric states - the quasi-biennial oscillation (QBO) which impacts zonal movement of the stratospheric volcanic plume - to estimate the phase of the QBO in 1883 required for a fast-moving westward cloud. Since this alone is unable to match the observed latitudinal spread of the aerosols, we then explore the impact of an&#160; umbrella cloud (2000 km diameter) that almost certainly formed during such a large eruption. A large umbrella cloud, spreading over ~18 degrees within the duration of the climax of the eruption (6-8 hours), can lead to much quicker latitudinal spread than a point source (vent). We will discuss the results of the combined model (umbrella cloud and correct QBO phase) with historical accounts and observations, as well as previous work on the 1991 Pinatubo eruption. We also consider the likely impacts of water on aerosol concentrations and the relevance of this process for eruptions with possible significant seawater interactions, like Krakatau. We posit that the role of umbrella clouds is an under-appreciated, but significant, process for beginning to model the climatic impacts of large volcanic eruptions.

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Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in the EC-Earth global climate model

Geoscientific Model Development ◽

10.5194/gmd-10-1383-2017 ◽

2017 ◽

Vol 10 (3) ◽

pp. 1383-1402 ◽

Cited By ~ 35

Author(s):

Paolo Davini ◽

Jost von Hardenberg ◽

Susanna Corti ◽

Hannah M. Christensen ◽

Stephan Juricke ◽

...

Keyword(s):

High Resolution ◽

Large Scale ◽

Climate Model ◽

Global Climate ◽

Rainfall Variability ◽

Global Climate Model ◽

Small Scale ◽

Low Resolution ◽

The Impact ◽

Stochastic Physics

Abstract. The Climate SPHINX (Stochastic Physics HIgh resolutioN eXperiments) project is a comprehensive set of ensemble simulations aimed at evaluating the sensitivity of present and future climate to model resolution and stochastic parameterisation. The EC-Earth Earth system model is used to explore the impact of stochastic physics in a large ensemble of 30-year climate integrations at five different atmospheric horizontal resolutions (from 125 up to 16 km). The project includes more than 120 simulations in both a historical scenario (1979–2008) and a climate change projection (2039–2068), together with coupled transient runs (1850–2100). A total of 20.4 million core hours have been used, made available from a single year grant from PRACE (the Partnership for Advanced Computing in Europe), and close to 1.5 PB of output data have been produced on SuperMUC IBM Petascale System at the Leibniz Supercomputing Centre (LRZ) in Garching, Germany. About 140 TB of post-processed data are stored on the CINECA supercomputing centre archives and are freely accessible to the community thanks to an EUDAT data pilot project. This paper presents the technical and scientific set-up of the experiments, including the details on the forcing used for the simulations performed, defining the SPHINX v1.0 protocol. In addition, an overview of preliminary results is given. An improvement in the simulation of Euro-Atlantic atmospheric blocking following resolution increase is observed. It is also shown that including stochastic parameterisation in the low-resolution runs helps to improve some aspects of the tropical climate – specifically the Madden–Julian Oscillation and the tropical rainfall variability. These findings show the importance of representing the impact of small-scale processes on the large-scale climate variability either explicitly (with high-resolution simulations) or stochastically (in low-resolution simulations).

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

The Journal of Agricultural Science ◽

10.1017/s0021859616000654 ◽

2016 ◽

Vol 155 (3) ◽

pp. 407-420 ◽

Cited By ~ 7

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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Downscaling Atmosphere-Ocean Global Climate Model Precipitation Simulations over Africa Using Bias-Corrected Lateral and Lower Boundary Conditions

Atmosphere ◽

10.3390/atmos9120493 ◽

2018 ◽

Vol 9 (12) ◽

pp. 493 ◽

Cited By ~ 2

Author(s):

Leonard Druyan ◽

Matthew Fulakeza

Keyword(s):

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Regional Climate ◽

Lower Boundary ◽

Climate Projections ◽

African Easterly Jet ◽

Modèle Simulation ◽

Goddard Institute ◽

Bias Corrections

A prequel study showed that dynamic downscaling using a regional climate model (RCM) over Africa improved the Goddard Institute for Space Studies Atmosphere-Ocean Global Climate Model (GISS AOGCM: ModelE) simulation of June–September rainfall patterns over Africa. The current study applies bias corrections to the lateral and lower boundary data from the AOGCM driving the RCM, based on the comparison of a 30-year simulation to the actual climate. The analysis examines the horizontal pattern of June–September total accumulated precipitation, the time versus latitude evolution of zonal mean West Africa (WA) precipitation (showing monsoon onset timing), and the latitude versus altitude cross-section of zonal winds over WA (showing the African Easterly Jet and the Tropical Easterly Jet). The study shows that correcting for excessively warm AOGCM Atlantic sea-surface temperatures (SSTs) improves the simulation of key features, whereas applying 30-year mean bias corrections to atmospheric variables driving the RCM at the lateral boundaries does not improve the RCM simulations. We suggest that AOGCM climate projections for Africa should benefit from downscaling by nesting an RCM that has demonstrated skill in simulating African climate, driven with bias-corrected SST.

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Dust Aerosol Important for Snowball Earth Deglaciation

Journal of Climate ◽

10.1175/2010jcli3378.1 ◽

2010 ◽

Vol 23 (15) ◽

pp. 4121-4132 ◽

Cited By ~ 26

Author(s):

Dorian S. Abbot ◽

Itay Halevy

Keyword(s):

Climate Models ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Atmospheric Model ◽

Dust Aerosol ◽

Snowball Earth ◽

Dust Aerosols ◽

Co2 Levels ◽

The Impact

Abstract Most previous global climate model simulations could only produce the termination of Snowball Earth episodes at CO2 partial pressures of several tenths of a bar, which is roughly an order of magnitude higher than recent estimates of CO2 levels during and shortly after Snowball events. These simulations have neglected the impact of dust aerosols on radiative transfer, which is an assumption of potentially grave importance. In this paper it is argued, using the Dust Entrainment and Deposition (DEAD) box model driven by GCM results, that atmospheric dust aerosol concentrations may have been one to two orders of magnitude higher during a Snowball Earth event than today. It is furthermore asserted on the basis of calculations using NCAR’s Single Column Atmospheric Model (SCAM)—a radiative–convective model with sophisticated aerosol, cloud, and radiative parameterizations—that when the surface albedo is high, such increases in dust aerosol loading can produce several times more surface warming than an increase in the partial pressure of CO2 from 10−4 to 10−1 bar. Therefore the conclusion is reached that including dust aerosols in simulations may reconcile the CO2 levels required for Snowball termination in climate models with observations.

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Temperature decrease through the Eocene-Oligocene transition controls eco-hydrologic shifts in Central Asia

10.5194/egusphere-egu2020-10034 ◽

2020 ◽

Author(s):

Alexander Rohrmann ◽

Guillaume Dupont-Nivet ◽

Michael Hren ◽

Dirk Sachse ◽

Niels Meijer ◽

...

Keyword(s):

Central Asia ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Temperature Drop ◽

Precipitation Amount ◽

Central China ◽

Broad Leaf ◽

Xining Basin ◽

The Impact

At ca. 34 Ma the Eocene-Oligocene transition (EOT) marks the shift from greenhouse conditions during the Eocene to the icehouse of the Oligocene and was the most pronounced cooling event during the Cenozoic. This event is well documented in marine records with a significant increase in benthic foraminifera &#948;18O values suggesting a 5&#176;C cooling in air temperature through the EOT. Instead, the few but growing number of terrestrial records suggest a much larger cooling of 4-9&#176;C. Yet, details regarding the exact timing of cooling and ensuing terrestrial changes in climate, hydrology, and ecology are sparse. Here, we investigate the impact of the EOT cooling event and associated climatic changes on the hydrology and vegetation in central China. We use stable isotopes of hydrogen (&#948;Dwax) and carbon (&#948;13Cwax) from leaf-waxes, a paleo-hydrology proxy obtained from organic material in sedimentary rocks, in combination with pollen data from a continuous well-dated, high-resolution sedimentary section from the Xining Basin in NE Tibet (36&#176;42' N, 101&#176;43' E). We then compare our results to a fully-coupled, global climate model (GCM) simulating the pre- and post-EOT conditions in central Asia.The obtained &#948;Dwax record ranges between -160 to -190&#8240; and shows a complex two-step transition through the EOT with a rapid initial drop of -30&#8240; from 33.9 to 33.7 Ma, a recovery to pre-EOT values between 33.7 to 33.4 Ma and a second drop similar in magnitude as the first one. In contrast, &#948;13Cwax values remain unchanged at -29 to -28&#8240; through the EOT. The GCM indicates a difference in temperature throughout the year between pre- and post-EOT runs of 8-9&#176;C at the Xining Basin with change in seasonality due to the collapse of the pre-EOT wet spring season, yielding mainly autumn precipitation after the transition. The overall precipitation amount remained in both simulations dry with < 500 mm/yr. The combined results show that the region experienced: (a) a significant temperature drop of 8-9&#176;C through the EOT being the first-order control on the records decrease in &#948;Dwax&#160; (1-2 &#8240; per 1&#176;C in mid-latitudes and up-to 5 &#8240; per 1&#176;C in higher latitudes) through the EOT; (b) constant bioproductivity and/or similar water-use efficiency within plants displayed by unchanged &#948;13Cwax values; (c) a changeover from a &#8220;warm-wet&#8221; desert abundant in Nitraria and Ephedra shrubs to a &#8220;temperate&#8221; desert with an expansion of conifers and broad-leaf trees in the higher-elevation hinterlands. We interpret that this change in seasonality and cooler EOT temperatures reduced the plant&#8217;s overall transpirational pressure, contributing to the spread of conifers and broad-leaf trees after the EOT under regionally new hydrologic conditions.

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Constraining the model representation of the aerosol life cycle in relation to sources and sinks.

10.5194/egusphere-egu2020-21948 ◽

2020 ◽

Author(s):

Paul Kim ◽

Daniel Partridge ◽

James Haywood

Keyword(s):

Climate Change ◽

Life Cycle ◽

Large Scale ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Evaluation Framework ◽

Microphysical Properties ◽

The Impact ◽

Source And Sink

Global climate model (GCM) ensembles still produce a significant spread of estimates for the future of climate change which hinders our ability to influence policymakers. The range of these estimates can only partly be explained by structural differences and varying choice of parameterisation schemes between GCMs. GCM representation of cloud and aerosol processes, more specifically aerosol microphysical properties, remain a key source of uncertainty contributing to the wide spread of climate change estimates. The radiative effect of aerosol is directly linked to the microphysical properties and these are in turn controlled by aerosol source and sink processes during transport as well as meteorological conditions.A Lagrangian, trajectory-based GCM evaluation framework, using spatially and temporally collocated aerosol diagnostics, has been applied to over a dozen GCMs via the AeroCom initiative. This framework is designed to isolate the source and sink processes that occur during the aerosol life cycle in order to improve the understanding of the impact of these processes on the simulated aerosol burden. Measurement station observations linked to reanalysis trajectories are then used to evaluate each GCM with respect to a quasi-observational standard to assess GCM skill. The AeroCom trajectory experiment specifies strict guidelines for modelling groups; all simulations have wind fields nudged to ERA-Interim reanalysis and all simulations use emissions from the same inventories. This ensures that the discrepancies between GCM parameterisations are emphasised and differences due to large scale transport patterns, emissions and other external factors are minimised.Preliminary results from the AeroCom trajectory experiment will be presented and discussed, some of which are summarised now. A comparison of GCM aerosol particle number size distributions against observations made by measurement stations in different environments will be shown, highlighting the difficulties that GCMs have at reproducing observed aerosol concentrations across all size ranges in pristine environments. The impact of precipitation during transport on aerosol microphysical properties in each GCM will be shown and the implications this has on resulting aerosol forcing estimates will be discussed. Results demonstrating the trajectory collocation framework will highlight its ability to give more accurate estimates of the key aerosol sources in GCMs and the importance of these sources in influencing modelled aerosol-cloud effects. In summary, it will be shown that this analysis approach enables us to better understand the drivers behind inter-model and model-observation discrepancies.

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