scholarly journals Robust Future Changes in Meteorological Drought in CMIP6 Projections Despite Uncertainty in Precipitation

2021 ◽  
Author(s):  
Anna Ukkola ◽  
Martin De Kauwe ◽  
Michael Roderick ◽  
Gab Abramowitz ◽  
Andy Pitman
Keyword(s):  
Climate Models ◽  
Water Security ◽  
Meteorological Drought ◽  
Resource Planning ◽  
Climate Projections ◽  
Land Area ◽  
Natural Ecosystems ◽  
Drought Duration ◽  
Drought Intensity ◽  
Projected Changes

<p>Understanding how climate change affects droughts guides adaptation planning in agriculture, water security, and ecosystem management. Earlier climate projections have highlighted high uncertainty in future drought projections, hindering effective planning. We use the latest CMIP6 projections and find more robust projections of meteorological drought compared to mean precipitation. We find coherent projected changes in seasonal drought duration and frequency (robust over >45% of the global land area), despite a lack of agreement across models in projected changes in mean precipitation (24% of the land area). Future drought changes are larger and more consistent in CMIP6 compared to CMIP5. We find regionalised increases and decreases in drought duration and frequency that are driven by changes in both precipitation mean and variability. Conversely, drought intensity increases over most regions but is not simulated well historically by the climate models. These more robust projections of meteorological drought in CMIP6 provide clearer direction for water resource planning and the identification of agricultural and natural ecosystems at risk.</p>

Understanding changes in meteorological drought in regional UK Climate Projections (UKCP18)

2021 ◽  
Author(s):  
Nele Reyniers ◽  
Nans Addor ◽  
Geoff Darch ◽  
Yi He ◽  
Qianyu Zha ◽  
...  
Keyword(s):  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Horizontal Resolution ◽  
Economic Damage ◽  
Climate Projections ◽  
Potential Evaporation ◽  
Drought Duration ◽  
Projected Changes ◽  
The Impact ◽  
Meteorological Droughts

<div> <p>Extreme droughts can cause enormous ecological and economic damage, and are expected to become more severe in some regions due to climate change. For water managers, it is crucial to understand extreme droughts and how they are projected to change compared to previous droughts, in order to plan for resilience to these events. </p> </div><div> <p>Changes in water resources do not only result from changes in precipitation and periods of below normal precipitation (meteorological droughts), they are also shaped by changes in atmospheric moisture demand, characterized here by potential evaporation. Therefore we use two standardized indicators, the Standardized Precipitation Index (SPI) and the Standardized Precipitation-Evaporation Index (SPEI) to isolate the impact of projected changes in precipitation and potential evaporation. We consider the contribution of precipitation deficits and potential evaporation changes to projected changes in future drought duration, severity and frequency. We explore droughts and their development across different time scales, as their diversity – from flash droughts to creeping multi-year droughts – adds to the challenge.</p> <p>We make use of the recently released 12-member 12-km horizontal resolution perturbed parameter ensemble of spatially coherent regional UKCP18 climate projections (with and without bias adjustment). This ensemble of projections was produced by the UK Met Office by dynamically downscaling a perturbed parameter ensemble of HadGEM3-GC3.05 simulations with a regional variant. The skill of the UKCP18 regional ensemble members for drought simulation is evaluated by comparison with observed drought metrics for the baseline period.  <br>Projected changes in UK climate according to the UKCP18 projections include wetter winters, drier summers and generally stronger temperature increases in summer than in winter. We assess how these changes contribute to changes in drought characteristics using SPI and SPEI for each member of the ensemble. </p> </div><div> <p>While this work focusses on meteorological droughts, it will be followed by a future analysis of their propagation to hydrological droughts. This project aims to support adaptation to droughts in the region of East Anglia and is conducted in collaboration with the water company Anglian Water. </p> </div>

scholarly journals Spatiotemporal Characteristics of Meteorological Drought During the Past Half Century in Different Climates Over Iran

2022 ◽  
Author(s):  
Mehdi Mohammadi Ghaleni ◽  
Saeed Sharafi ◽  
Seyed-Mohammad Hosseini-Moghari ◽  
Jalil Helali ◽  
Ebrahim Asadi Oskouei
Keyword(s):  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Drought Indices ◽  
Drought Duration ◽  
Drought Intensity ◽  
Half Century ◽  
Past Half Century ◽  
Term Data

Abstract The present study compares the main characteristics (intensity, duration, and frequency) of meteorological drought events in the four climates (Hyperarid, Arid, Semiarid, and Humid) of Iran. For this purpose, three drought indices, including Standardized Precipitation Index (SPI), Reconnaissance Drought Index (RDI), and Standardized Precipitation Evapotranspiration Index (SPEI), were employed at the timescales of 1-, 3-, 6-, 9- and 12-months. These indices were compared by utilizing long-term data of 41 synoptic meteorological stations for the recent half century, 1969–2019. The long-term analysis of drought indices indicates that the duration and intensity of drought events have temporally risen after the 1998–99 period. Iran has experienced the longest duration (40 months) of extreme drought during Dec 98–Mar 02 and Jan 18–Mar 18, respectively. Spatial patterns demonstrate that drought intensity uniformly increased in SPI1 to SPI12, and SPEI3 to SPEI12, from humid and semiarid to arid and hyperarid regions. The average drought duration in studied stations for SPI, SPEI and RDI indices equaled 9, 12, and 9 months, respectively. In addition, mean drought frequencies are calculated at 14, 17, and 13 percent for SPI, SPEI and RDI indices, respectively. Generally, SPEI compared to SPI and RDI shows greater duration and frequency of drought events, particularly in arid and hyperarid regions. The research shows the crucial role of climatic variables in detecting drought characteristics and the importance of selecting appropriate drought indices in various climates.

scholarly journals Climate change impacts on the seasonality and generation processes of floods – projections and uncertainties for catchments with mixed snowmelt/rainfall regimes

2015 ◽  
Vol 19 (2) ◽  
pp. 913-931 ◽  
Author(s):  
K. Vormoor ◽  
D. Lawrence ◽  
M. Heistermann ◽  
A. Bronstert
Keyword(s):  
Climate Change ◽  
Production Management ◽  
Climate Models ◽  
Hydrological Model ◽  
Climate Model ◽  
Climate Projections ◽  
High Mountain ◽  
Relative Role ◽  
Projected Changes ◽  
Rainfall Regimes

Abstract. Climate change is likely to impact the seasonality and generation processes of floods in the Nordic countries, which has direct implications for flood risk assessment, design flood estimation, and hydropower production management. Using a multi-model/multi-parameter approach to simulate daily discharge for a reference (1961–1990) and a future (2071–2099) period, we analysed the projected changes in flood seasonality and generation processes in six catchments with mixed snowmelt/rainfall regimes under the current climate in Norway. The multi-model/multi-parameter ensemble consists of (i) eight combinations of global and regional climate models, (ii) two methods for adjusting the climate model output to the catchment scale, and (iii) one conceptual hydrological model with 25 calibrated parameter sets. Results indicate that autumn/winter events become more frequent in all catchments considered, which leads to an intensification of the current autumn/winter flood regime for the coastal catchments, a reduction of the dominance of spring/summer flood regimes in a high-mountain catchment, and a possible systematic shift in the current flood regimes from spring/summer to autumn/winter in the two catchments located in northern and south-eastern Norway. The changes in flood regimes result from increasing event magnitudes or frequencies, or a combination of both during autumn and winter. Changes towards more dominant autumn/winter events correspond to an increasing relevance of rainfall as a flood generating process (FGP) which is most pronounced in those catchments with the largest shifts in flood seasonality. Here, rainfall replaces snowmelt as the dominant FGP primarily due to increasing temperature. We further analysed the ensemble components in contributing to overall uncertainty in the projected changes and found that the climate projections and the methods for downscaling or bias correction tend to be the largest contributors. The relative role of hydrological parameter uncertainty, however, is highest for those catchments showing the largest changes in flood seasonality, which confirms the lack of robustness in hydrological model parameterization for simulations under transient hydrometeorological conditions.

scholarly journals Adaptation of water resource systems to an uncertain future

2015 ◽  
Vol 12 (9) ◽  
pp. 8853-8889 ◽  
Author(s):  
C. L. Walsh ◽  
S. Blenkinsop ◽  
H. J. Fowler ◽  
A. Burton ◽  
R. J. Dawson ◽  
...  
Keyword(s):  
Water Resources ◽  
Population Growth ◽  
Water Resource ◽  
Water Resource Management ◽  
Climate Models ◽  
Resource Planning ◽  
Integrated Modelling ◽  
Climate Projections ◽  
Changing Climate ◽  
Adaptation Options

Abstract. Globally, water resources management faces significant challenges from changing climate and growing populations. At local scales, the information provided by climate models is insufficient to support the water sector in making future adaptation decisions. Furthermore, projections of change in local water resources are wrought with uncertainties surrounding natural variability, future greenhouse gas emissions, model structure, population growth and water consumption habits. To analyse the magnitude of these uncertainties, and their implications for local scale water resource planning, we present a top-down approach for testing climate change adaptation options using probabilistic climate scenarios and demand projections. An integrated modelling framework is developed which implements a new, gridded spatial weather generator, coupled with a rainfall-runoff model and water resource management simulation model. We use this to provide projections of the number of days, and associated uncertainty that will require implementation of demand saving measures such as hose pipe bans and drought orders. Results, which are demonstrated for the Thames basin, UK, indicate existing water supplies are sensitive to a changing climate and an increasing population, and that the frequency of severe demand saving measures are projected to increase. Considering both climate projections and population growth the median number of drought order occurrences may increase five-fold. The effectiveness of a range of demand management and supply options have been tested and shown to provide significant benefits in terms of reducing the number of demand saving days. We found that increased supply arising from various adaptation options may compensate for increasingly variable flows; however, without reductions in overall demand for water resources such options will be insufficient on their own to adapt to uncertainties in the projected changes in climate and population. For example, a 30 % reduction in overall demand by 2050 has a greater impact on reducing the frequency of drought orders than any of the individual or combinations of supply options; hence a portfolio of measures are required.

scholarly journals A Proposal to Evaluate Drought Characteristics Using Multiple Climate Models for Multiple Timescales

Climate ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 79 ◽  
Author(s):  
Nguyen Tien Thanh
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Global Climate Models ◽  
Precipitation Index ◽  
Climate Projections ◽  
Rcp Scenarios ◽  
Multiple Timescales ◽  
Drought Characteristics

This study presents a method to investigate meteorological drought characteristics using multiple climate models for multiple timescales under two representative concentration pathway (RCP) scenarios, RCP4.5 and RCP8.5, during 2021–2050. The methods of delta change factor, unequal weights, standardized precipitation index, Mann–Kendall and Sen’s slope are proposed and applied with the main purpose of reducing uncertainty in climate projections and detection of the projection trends in meteorological drought. Climate simulations of three regional climate models driven by four global climate models are used to estimate weights for each run on the basic of rank sum. The reliability is then assessed by comparing a weighted ensemble climate output with observations during 1989–2008. Timescales of 1, 3, 6, 9, 12, and 24 months are considered to calculate the standardized precipitation index, taking the Vu Gia-Thu Bon (VG-TB) as a pilot basin. The results show efficient precipitation simulations using unequal weights. In the same timescales, the occurrence of moderately wet events is smaller than that of moderately dry events under the RCP4.5 scenario during 2021–2050. Events classified as “extremely wet”, “extremely dry”, “very wet” and “severely dry” are expected to rarely occur under the RCP8.5 scenario.

Fine-Scale Climate Projections for Africa: What Additional Robust Spatial Detail is Provided by a Convection-Permitting Model?  

2021 ◽  
Author(s):  
Dave Rowell ◽  
Segolene Berthou
Keyword(s):  
Climate Models ◽  
Spatial Scales ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Future Climate Change ◽  
Climate Projections ◽  
Fine Scale ◽  
Climate Data ◽  
Tropical Regions ◽  
Projected Changes

<p>Regional climate projections using ultra-high resolution convection-permitting (CP) models are now increasingly available, with recent endeavours also focussing on vulnerable tropical regions. A number of recent studies have examined a pair of pan-Africa integrations of the Met Office CP model (CP4A), run at 4.4km resolution with 10 years of both a present-day simulation and a circa-2100 projection. However, experience from inter-disciplinary discussions has revealed different perspectives on the value of such experiments, with climate scientists emphasising the importance of an improved representation of convection, whereas applied scientists emphasise the importance of the unprecedented spatial scale of the available climate data. This raises critical questions about the usable spatial scales of such projections. Can CP models really provide robust information about future climate change at finer scales than parameterised regional climate models? We address this question with a focus on projected changes in rainfall, both seasonal means and daily extremes, both of which may be expected to exhibit heterogeneous climate responses in regions of large surface forcing. Although the capacity for statistically significant detail is found to be small in this short projection, detectable sub-25km variability is indeed apparent in regions of high topographic variability. Coastal regions, such as lakes and marine bays are also examined, along with urban boundaries. Furthermore, where no significant fine-scale detail is apparent (spatial heterogeneity is only due to sampling variability), we also examine the extent to which the robustness of climate information (better signal-to-noise ratios) can be enhanced for users by the spatial aggregation of model data.</p>

scholarly journals A 3D Copula Method for the Impact and Risk Assessment of Drought Disaster and an Example Application

2021 ◽  
Vol 9 ◽  
Author(s):  
Wei Hou ◽  
Pengcheng Yan ◽  
Guolin Feng ◽  
Dongdong Zuo
Keyword(s):  
Risk Assessment ◽  
Meteorological Drought ◽  
Theory And Practice ◽  
Agricultural Drought ◽  
Risk Assessments ◽  
Drought Risk ◽  
Drought Event ◽  
Drought Duration ◽  
Drought Intensity ◽  
The Impact

Droughts have more impact on crops than any other natural disaster. Therefore, drought risk assessments, especially quantitative drought risk assessments, are significant in order to understand and reduce the negative impacts associated with droughts, and a quantitative risk assessment includes estimating the probability and consequences of hazards. In order to achieve this goal, we built a model based on the three-dimensional (3D) Copula function for the assessment of the proportion of affected farmland areas (PAFA) based on the idea of internally combining the drought duration, drought intensity, and drought impact. This model achieves the “internal combination” of drought characteristics and drought impacts rather than an “external combination.” The results of this model are not only able to provide the impacts at different levels that a drought event (drought duration and drought intensity) may cause, but are also able to show the occurrence probability of impact at each particular level. We took Huize County and Mengzi County in Yunnan Province as application examples based on the meteorological drought index (SPI), and the results showed that the PAFAs obtained by the method proposed in this paper were basically consistent with the actual PAFAs in the two counties. Moreover, due to the meteorological drought always occurring before an agricultural drought, we can get SPI predictions for the next month or months and can further obtain more abundant information on a drought warning and its impact. Therefore, the method proposed in this paper has values both on theory and practice.

Regional Climate Scenarios for use in Nordic Water Resources Studies

2003 ◽  
Vol 34 (5) ◽  
pp. 399-412 ◽  
Author(s):  
M. Rummukainen ◽  
J. Räisänen ◽  
D. Bjørge ◽  
J.H. Christensen ◽  
O.B. Christensen ◽  
...  
Keyword(s):  
Water Resources ◽  
Climate Models ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Projections ◽  
Climate Scenarios ◽  
Soil Frost ◽  
Nordic Region ◽  
Regional Climate Projections

According to global climate projections, a substantial global climate change will occur during the next decades, under the assumption of continuous anthropogenic climate forcing. Global models, although fundamental in simulating the response of the climate system to anthropogenic forcing are typically geographically too coarse to well represent many regional or local features. In the Nordic region, climate studies are conducted in each of the Nordic countries to prepare regional climate projections with more detail than in global ones. Results so far indicate larger temperature changes in the Nordic region than in the global mean, regional increases and decreases in net precipitation, longer growing season, shorter snow season etc. These in turn affect runoff, snowpack, groundwater, soil frost and moisture, and thus hydropower production potential, flooding risks etc. Regional climate models do not yet fully incorporate hydrology. Water resources studies are carried out off-line using hydrological models. This requires archived meteorological output from climate models. This paper discusses Nordic regional climate scenarios for use in regional water resources studies. Potential end-users of water resources scenarios are the hydropower industry, dam safety instances and planners of other lasting infrastructure exposed to precipitation, river flows and flooding.

scholarly journals Sensitivity of projected climate impacts to climate model weighting: multi-sector analysis in eastern Africa

2021 ◽  
Vol 164 (3-4) ◽  
Author(s):  
Seshagiri Rao Kolusu ◽  
Christian Siderius ◽  
Martin C. Todd ◽  
Ajay Bhave ◽  
Declan Conway ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Investment Decisions ◽  
Climate Impacts ◽  
Future Climate ◽  
Eastern Africa ◽  
Climate Projections ◽  
Systematic Effect ◽  
Risk Profiles ◽  
Model Weighting

AbstractUncertainty in long-term projections of future climate can be substantial and presents a major challenge to climate change adaptation planning. This is especially so for projections of future precipitation in most tropical regions, at the spatial scale of many adaptation decisions in water-related sectors. Attempts have been made to constrain the uncertainty in climate projections, based on the recognised premise that not all of the climate models openly available perform equally well. However, there is no agreed ‘good practice’ on how to weight climate models. Nor is it clear to what extent model weighting can constrain uncertainty in decision-relevant climate quantities. We address this challenge, for climate projection information relevant to ‘high stakes’ investment decisions across the ‘water-energy-food’ sectors, using two case-study river basins in Tanzania and Malawi. We compare future climate risk profiles of simple decision-relevant indicators for water-related sectors, derived using hydrological and water resources models, which are driven by an ensemble of future climate model projections. In generating these ensembles, we implement a range of climate model weighting approaches, based on context-relevant climate model performance metrics and assessment. Our case-specific results show the various model weighting approaches have limited systematic effect on the spread of risk profiles. Sensitivity to climate model weighting is lower than overall uncertainty and is considerably less than the uncertainty resulting from bias correction methodologies. However, some of the more subtle effects on sectoral risk profiles from the more ‘aggressive’ model weighting approaches could be important to investment decisions depending on the decision context. For application, model weighting is justified in principle, but a credible approach should be very carefully designed and rooted in robust understanding of relevant physical processes to formulate appropriate metrics.

scholarly journals New Approach for Bias Correction and Stochastic Downscaling of Future Projections for Daily Mean Temperatures to a High-Resolution Grid

2019 ◽  
Vol 58 (12) ◽  
pp. 2617-2632 ◽  
Author(s):  
Qifen Yuan ◽  
Thordis L. Thorarinsdottir ◽  
Stein Beldring ◽  
Wai Kwok Wong ◽  
Shaochun Huang ◽  
...  
Keyword(s):  
High Resolution ◽  
Bias Correction ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Change Signal ◽  
Climate Projections ◽  
Data Product ◽  
Temporal Features ◽  
Stochastic Downscaling

AbstractIn applications of climate information, coarse-resolution climate projections commonly need to be downscaled to a finer grid. One challenge of this requirement is the modeling of subgrid variability and the spatial and temporal dependence at the finer scale. Here, a postprocessing procedure for temperature projections is proposed that addresses this challenge. The procedure employs statistical bias correction and stochastic downscaling in two steps. In the first step, errors that are related to spatial and temporal features of the first two moments of the temperature distribution at model scale are identified and corrected. Second, residual space–time dependence at the finer scale is analyzed using a statistical model, from which realizations are generated and then combined with an appropriate climate change signal to form the downscaled projection fields. Using a high-resolution observational gridded data product, the proposed approach is applied in a case study in which projections of two regional climate models from the Coordinated Downscaling Experiment–European Domain (EURO-CORDEX) ensemble are bias corrected and downscaled to a 1 km × 1 km grid in the Trøndelag area of Norway. A cross-validation study shows that the proposed procedure generates results that better reflect the marginal distributional properties of the data product and have better consistency in space and time when compared with empirical quantile mapping.

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