Underestimation of temperature variability in weather generators and implications for the representation of extreme temperatures in downscaled climate change scenarios

2020 ◽  
Author(s):  
Pierluigi Calanca
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Extreme Values ◽  
Climatic Variability ◽  
Model Performance ◽  
Maximum Temperature ◽  
Climate Change Scenarios ◽  
Modes Of Variability ◽  
Weather Generators ◽  
Total Variability

<p>Stochastic weather generators are still widely used for downscaling climate change scenarios, in particular in the context of agricultural and hydrological impact assessments. Their performance is in many respects satisfactory, except perhaps for the fact that they fail to represent climatic variability in an adequate way. This has implications for the representation of extreme values and their statistics. Concerning precipitation, different approaches for amending this situation have proposed in the past, including using more sophisticated models to better simulate the persistence of wet and dry spells, conditioning rainfall-generating parameters on indices of the large-scale atmospheric circulation, or employing autoregressive models to represent year-to-year variations in annual precipitation amounts. With regard to (minimum and maximum) temperature, efforts to address the question of why weather generators underestimate total variability have been less systematic. Based on results obtained with a well-known weather generator (LARS-WG), this contribution aims to discuss which modes of variability are missing and why, elaborate on the implications of underrepresenting temperature variance for the simulation of temperature extremes in downscaled climate change scenarios, and suggest options to tackle the problem and improve the model performance.</p>

Potential state shifts in terrestrial ecosystems related to changes in El Niño-Southern Oscillation dynamics

2020 ◽  
Author(s):  
Mateo Duque-Villegas ◽  
Juan Fernando Salazar ◽  
Angela Maria Rendón
Keyword(s):  
Large Scale ◽  
Climate Model ◽  
Extreme Values ◽  
Southern Oscillation ◽  
Climatic Variability ◽  
Terrestrial Ecosystems ◽  
Eastern Africa ◽  
State Transitions ◽  
Climate Change Scenarios ◽  
Earth’S Climate

<p>The El Niño-Southern Oscillation (ENSO) phenomenon is regarded as a policy-relevant tipping element of the Earth's climate system. It has a prominent planetary-scale influence on climatic variability and it is susceptible to anthropogenic forcing, which could alter irreversibly its dynamics. Changes in frequency and/or amplitude of ENSO would have major implications for terrestrial hydrology and ecosystems. The amount of extreme events such as droughts and floods could vary regionally, as well as their intensities. Here, we use an intermediate complexity climate model, namely the Planet Simulator (PlaSim), to study the potential impact on Earth's climate and its terrestrial ecosystems of changing ENSO dynamics in a couple of experiments. Initially we investigate the global effects of a permanent El Niño, and then we analyse changes in the amplitude of the fluctuation. We found that PlaSim model yields a sensible representation of current large-scale climatological patterns, including ENSO-related variability, as well as realistic estimates of global energy and water budgets. For the permanent El Niño state, there were significant differences in the global distribution of water and energy fluxes that led to asymmetrical effects on vegetation production, which increased in the tropics and decreased in temperate regions. In terrestrial ecosystems of regions such as western North America, the Amazon rainforest, south-eastern Africa and Australia, we found that these El Niño-induced changes could be associated with biome state transitions. Particularly for Australia, we found country-wide aridification as a result of sustained El Niño conditions, which is a potential state in which recent wildfires would be even more dramatic. When the amplitude of the ENSO fluctuation changes, we found that although mean climatological values do not change significantly, extreme values of variables such as temperature and precipitation become more extreme. Our approach aims at recognizing potential threats for terrestrial ecosystems in climate change scenarios in which there are more frequent El Niño phenomena or the intensities of the ENSO phases change. Although it is not enough to prove such effects will be observed, we show a consistent picture and it should raise awareness about conservation of global ecosystems.</p>

Future changes of circulation types associated with extremes over Sweden

2020 ◽  
Author(s):  
Felicitas Hansen ◽  
Danijel Belusic ◽  
Klaus Wyser
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Radiative Forcing ◽  
Large Scale ◽  
Extreme Values ◽  
Global Climate Model ◽  
Historical Period ◽  
Climate Change Scenarios ◽  
Circulation Types ◽  
Precipitation And Temperature

<p>The large-scale atmospheric circulation is one of the most important factors influencing weather and climate conditions on different timescales. Its short- and long-term changes considerably determine both mean and extreme values of surface parameters like temperature or precipitation rates. Future changes of circulation patterns are of particular interest as these may significantly alter or amplify the expected thermodynamic changes due to changing concentrations of greenhouse gases, albedo and land use. We analyse both historical as well as future climate simulations of the SMHI large ensemble (S-LENS) performed with the EC-Earth3 global climate model to examine large-scale circulation situations and their association to extremes in precipitation and temperature over Sweden. Various methods exist to classify mostly sea level pressure or geopotential height fields into characteristic circulation types, and we compare several of these methods for their applicability to represent precipitation and temperature variability over our region of interest. S-LENS consists of a 50-member ensemble for a historical period (1970-2014) and four 50-member climate change scenario ensembles covering the 21st century differing in terms of assumptions made for future radiative forcing development. We study the efficiency of circulation types in the historical period to give rise to extremes, and examine further the frequency and within-type changes of those circulation types associated with extremes by the middle and the end of the 21st century under the different climate change scenarios. S-LENS with its comparatively large number of both multi-decadal scenarios and realizations for each scenario serves as a perfect testbed to study potential changes in events of low frequency within the environment of a single model.</p>

scholarly journals Cenários de Mudanças Climáticas no Estado da Bahia através de Estudos Numéricos e Estatísticos (Climate Change Scenarios in Bahia through Numerical and Statistical Studies)

2013 ◽  
Vol 5 (5) ◽  
pp. 1019 ◽  
Author(s):  
Gildarte Barbosa Silva ◽  
Werônica Meira Souza ◽  
Pedro Vieira Azevedo
Keyword(s):  
Climate Change ◽  
Climatic Variability ◽  
Climatic Changes ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Climate Change Scenarios ◽  
Total Precipitation ◽  
Annual Total Precipitation ◽  
Annual Total ◽  
Statistical Studies

Este trabalho teve como objetivo investigar a ocorrência ou ausência de mudanças climáticas no período de 1970 a 2006, em algumas microrregiões do estado da Bahia: Irecê, Oeste, Sudoeste e Baixo Médio São Francisco, através de índices de tendências de mudanças climáticas obtidos da precipitação pluviométrica e das temperaturas máxima e mínima diárias das estações climatológicas das respectivas regiões e de cenários de mudanças climáticas. Utilizou-se os índices de detecção de mudanças climáticas sugeridos pela OMM calculados a partir dos dados de precipitação e das temperaturas máxima e mínima diárias através do software RClimdex 1.9.0. No estudo numérico foi utilizado o modelo BRAMS. Observou-se que na região de Irecê houve tendência de diminuição da precipitação total anual e aumento da intensidade das chuvas diárias. Na região Oeste houve aumento no número de dias com temperaturas elevadas, aumento nas temperaturas mínimas diárias e aumento na intensidade das chuvas. Na região Sudoeste houve uma  tendência de um pequeno aumento dos totais anuais de chuvas. Na região do Baixo Médio São Francisco houve aumento no número de dias com temperatura máxima diária, diminuição das chuvas diárias e da precipitação total anual. Essa variação na precipitação na região pode ser atribuída à circulação de grande escala, enquanto a intensidade das chuvas pode ter influência na variabilidade climática. Cabe aos gestores desse país encarar essa realidade com muita responsabilidade e, sugira ações e medidas eficazes para combatê-la, capacitando a sociedade como um todo para conviver com essa nova realidade. Palavras-chave: Mudanças climáticas; estudos numéricos; índices de tendências climáticas.   Climate Change Scenarios in Bahia through Numerical and Statistical Studies   ABSTRACT This work had as objective to investigate the occurrence or absence of climatic changes in the period of 1970 the 2006, in some microregions of the state of the Bahia: Irecê, Oeste, Sudoeste and Baixo Médio São Francisco, through indexes of trends of climatic changes with data of daily total precipitation and the daily temperatures maximum and minimum of the climatological stations of the respective regions and climate change scenarios. One used the indexes of detection of climatic changes suggested by WMO calculated from the data of daily precipitation and the daily temperature through software RClimdex 1.9.0. The study used numerical model BRAMS. It was observed that in the region of Irecê it had trend of reduction of the annual total precipitation and increase in the intensity of daily rains. In the region Oeste it had increase in the number of days with raised temperatures, increase in the daily minimum temperatures and increase in the intensity of rains. In the Sudeste region it had a trend of a small increase of the annual rain totals. In the region of the Baixo Médio São Francisco it had increase the number of days with daily maximum temperature, reduction of daily rains and the annual total precipitation. This variation in the precipitation in the region can be attributed to the circulation of great scale, while the intensity of rains can have influence in the climatic variability. It is the managers of this country face that reality as something that must be faced with great responsibility, and suggest actions and effective measures to combat it enabling the society as a whole to deal with this new reality.Keywords: Climatic changes; numerical studies; climate trends. 

Weather Generators

2020 ◽  
Author(s):  
Shuiqing Yin ◽  
Deliang Chen
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Large Scale ◽  
Extreme Values ◽  
Future Climate Change ◽  
Continuous Simulation ◽  
Weather Generators ◽  
Change Impact ◽  
Multiple Variables ◽  
Climate Time Series

Weather generators (WGs) are stochastic models that can generate synthetic climate time series of unlimited length and having statistical properties similar to those of observed time series for a location or an area. WGs can infill missing data, extend the length of climate time series, and generate meteorological conditions for unobserved locations. Since the 1990s WGs have become an important spatial-temporal statistical downscaling methodology and have been playing an increasingly important role in climate-change impact assessment. Although the majority of the existing WGs have focused on simulation of precipitation for a single site, more and more WGs considering correlations among multiple sites, and multiple variables, including precipitation and nonprecipitation variables such as temperature, solar radiation, wind, humidity, and cloud cover have been developed for daily and sub-daily scales. Various parametric, semi-parametric and nonparametric WGs have shown the ability to represent the mean, variance, and autocorrelation characteristics of climate variables at different scales. Two main methodologies including change factor and conditional WGs on large-scale dynamical and thermal dynamical weather states have been developed for applications under a changing climate. However, rationality and validity of assumptions underlining both methodologies need to be carefully checked before they can be used to project future climate change at local scale. Further, simulation of extreme values by the existing WGs needs to be further improved. WGs assimilating multisource observations from ground observations, reanalysis, satellite remote sensing, and weather radar for the continuous simulation of two-dimensional climate fields based on the mixed physics-based and stochastic approaches deserve further efforts. An inter-comparison project on a large ensemble of WG methods may be helpful for the improvement of WGs. Due to the applied nature of WGs, their future development also requires inputs from decision-makers and other relevant stakeholders.

Parameter transferability between multiple gridded input datasets challenges hydrological model performance under changing climate

2021 ◽  
Author(s):  
Moctar Dembélé ◽  
Bettina Schaefli ◽  
Grégoire Mariéthoz
Keyword(s):  
West Africa ◽  
Large Scale ◽  
Hydrological Model ◽  
Meteorological Data ◽  
Model Performance ◽  
Hydrologic Model ◽  
Hydrological Modelling ◽  
Climate Change Scenarios ◽  
Depth Analysis ◽  
Input Dataset

<p>The diversity of remotely sensed or reanalysis-based rainfall data steadily increases, which on one hand opens new perspectives for large scale hydrological modelling in data scarce regions, but on the other hand poses challenging question regarding parameter identification and transferability under multiple input datasets. This study analyzes the variability of hydrological model performance when (1) a set of parameters is transferred from the calibration input dataset to a different meteorological datasets and reversely, when (2) an input dataset is used with a parameter set, originally calibrated for a different input dataset.</p><p>The research objective is to highlight the uncertainties related to input data and the limitations of hydrological model parameter transferability across input datasets. An ensemble of 17 rainfall datasets and 6 temperature datasets from satellite and reanalysis sources (Dembélé et al., 2020), corresponding to 102 combinations of meteorological data, is used to force the fully distributed mesoscale Hydrologic Model (mHM). The mHM model is calibrated for each combination of meteorological datasets, thereby resulting in 102 calibrated parameter sets, which almost all give similar model performance. Each of the 102 parameter sets is used to run the mHM model with each of the 102 input datasets, yielding 10404 scenarios to that serve for the transferability tests. The experiment is carried out for a decade from 2003 to 2012 in the large and data-scarce Volta River basin (415600 km2) in West Africa.</p><p>The results show that there is a high variability in model performance for streamflow (mean CV=105%) when the parameters are transferred from the original input dataset to other input datasets (test 1 above). Moreover, the model performance is in general lower and can drop considerably when parameters obtained under all other input datasets are transferred to a selected input dataset (test 2 above). This underlines the need for model performance evaluation when different input datasets and parameter sets than those used during calibration are used to run a model. Our results represent a first step to tackle the question of parameter transferability to climate change scenarios. An in-depth analysis of the results at a later stage will shed light on which model parameterizations might be the main source of performance variability.</p><p>Dembélé, M., Schaefli, B., van de Giesen, N., & Mariéthoz, G. (2020). Suitability of 17 rainfall and temperature gridded datasets for large-scale hydrological modelling in West Africa. Hydrology and Earth System Sciences (HESS). https://doi.org/10.5194/hess-24-5379-2020</p>

scholarly journals Simulating future precipitation extremes in a complex Alpine catchment

2013 ◽  
Vol 13 (2) ◽  
pp. 263-277 ◽  
Author(s):  
C. Dobler ◽  
G. Bürger ◽  
J. Stötter
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Precipitation Extremes ◽  
Climate Projections ◽  
Research Station ◽  
Climate Change Scenarios ◽  
Station Data

Abstract. The objectives of the present investigation are (i) to study the effects of climate change on precipitation extremes and (ii) to assess the uncertainty in the climate projections. The investigation is performed on the Lech catchment, located in the Northern Limestone Alps. In order to estimate the uncertainty in the climate projections, two statistical downscaling models as well as a number of global and regional climate models were considered. The downscaling models applied are the Expanded Downscaling (XDS) technique and the Long Ashton Research Station Weather Generator (LARS-WG). The XDS model, which is driven by analyzed or simulated large-scale synoptic fields, has been calibrated using ECMWF-interim reanalysis data and local station data. LARS-WG is controlled through stochastic parameters representing local precipitation variability, which are calibrated from station data only. Changes in precipitation mean and variability as simulated by climate models were then used to perturb the parameters of LARS-WG in order to generate climate change scenarios. In our study we use climate simulations based on the A1B emission scenario. The results show that both downscaling models perform well in reproducing observed precipitation extremes. In general, the results demonstrate that the projections are highly variable. The choice of both the GCM and the downscaling method are found to be essential sources of uncertainty. For spring and autumn, a slight tendency toward an increase in the intensity of future precipitation extremes is obtained, as a number of simulations show statistically significant increases in the intensity of 90th and 99th percentiles of precipitation on wet days as well as the 5- and 20-yr return values.

scholarly journals Assessing runoff sensitivities to precipitation and temperature changes under global climate-change scenarios

2018 ◽  
Vol 50 (1) ◽  
pp. 24-42 ◽  
Author(s):  
Lei Chen ◽  
Jianxia Chang ◽  
Yimin Wang ◽  
Yuelu Zhu
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Yellow River ◽  
Control Variable ◽  
Maximum Temperature ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Temperature Changes ◽  
Runoff Change ◽  
Precipitation And Temperature

Abstract An accurate grasp of the influence of precipitation and temperature changes on the variation in both the magnitude and temporal patterns of runoff is crucial to the prevention of floods and droughts. However, there is a general lack of understanding of the ways in which runoff sensitivities to precipitation and temperature changes are associated with the CMIP5 scenarios. This paper investigates the hydrological response to future climate change under CMIP5 RCP scenarios by using the Variable Infiltration Capacity (VIC) model and then quantitatively assesses runoff sensitivities to precipitation and temperature changes under different scenarios by using a set of simulations with the control variable method. The source region of the Yellow River (SRYR) is an ideal area to study this problem. The results demonstrated that the precipitation effect was the dominant element influencing runoff change (the degree of influence approaching 23%), followed by maximum temperature (approaching 12%). The weakest element was minimum temperature (approaching 3%), despite the fact that the increases in minimum temperature were higher than the increases in maximum temperature. The results also indicated that the degree of runoff sensitivity to precipitation and temperature changes was subject to changing external climatic conditions.

scholarly journals Temperature trends in Fiji: a clear signal of climate change

2013 ◽  
Vol 31 (1) ◽  
pp. 27 ◽  
Author(s):  
Ravind Kumar ◽  
Mark Stephens ◽  
Tony Weir
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Pacific Islands ◽  
Extreme Values ◽  
Maximum Temperature ◽  
Temperature Trends ◽  
Clear Signal ◽  
Rate Of Increase ◽  
Significant Difference ◽  
Using Data

This paper analyses trends in temperature in Fiji, using data from more stations (10) and longer periods (52-78 years) than previous studies. All the stations analysed show a statistically significant trend in both maximum and minimum temperature, with increases ranging from 0.08 to 0.23°C per decade. More recent temperatures show a higher rate of increase, particularly in maximum temperature (0.18 to 0.69°C per decade from 1989 to 2008). This clear signal of climate change is consistent with that found in previous studies of temperatures in Fiji and other Pacific Islands. Trends in extreme values show an even stronger signal of climate change than that for mean temperatures. Our preliminary analysis of daily maxima at 6 stations indicates that for 4 of them (Suva, Labasa, Vunisea and Rotuma) there has been a tripling in the number of days per year with temperature >32°C between 1970 and 2008. The correlations between annual mean maximum (minimum) temperature and year are mostly strong: for about half the stations the correlation coefficient exceeds 60% over 50+ years. Trends do not vary systematically with location of station. At all 7 stations for which both trends are available there is no statistically significant difference between the trends in maximum and minimum temperatures.

scholarly journals Impacts of projected maximum temperature extremes for C21 by an ensemble of regional climate models on cereal cropping systems in the Iberian Peninsula

2011 ◽  
Vol 11 (12) ◽  
pp. 3275-3291 ◽  
Author(s):  
M. Ruiz-Ramos ◽  
E. Sánchez ◽  
C. Gallardo ◽  
M. I. Mínguez
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
High Temperatures ◽  
Climate Models ◽  
Cropping Systems ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Grain Filling ◽  
Maximum Temperature ◽  
Climate Change Scenarios

Abstract. Crops growing in the Iberian Peninsula may be subjected to damagingly high temperatures during the sensitive development periods of flowering and grain filling. Such episodes are considered important hazards and farmers may take insurance to offset their impact. Increases in value and frequency of maximum temperature have been observed in the Iberian Peninsula during the 20th century, and studies on climate change indicate the possibility of further increase by the end of the 21st century. Here, impacts of current and future high temperatures on cereal cropping systems of the Iberian Peninsula are evaluated, focusing on vulnerable development periods of winter and summer crops. Climate change scenarios obtained from an ensemble of ten Regional Climate Models (multimodel ensemble) combined with crop simulation models were used for this purpose and related uncertainty was estimated. Results reveal that higher extremes of maximum temperature represent a threat to summer-grown but not to winter-grown crops in the Iberian Peninsula. The study highlights the different vulnerability of crops in the two growing seasons and the need to account for changes in extreme temperatures in developing adaptations in cereal cropping systems. Finally, this work contributes to clarifying the causes of high-uncertainty impact projections from previous studies.

scholarly journals Tidal wetland resilience to sea level rise increases their carbon sequestration capacity in United States

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Faming Wang ◽  
Xiaoliang Lu ◽  
Christian J. Sanders ◽  
Jianwu Tang
Keyword(s):  
Climate Change ◽  
United States ◽  
Sea Level Rise ◽  
Sea Level ◽  
Large Scale ◽  
Accumulation Rate ◽  
C Sequestration ◽  
Tidal Wetlands ◽  
Tidal Wetland ◽  
Climate Change Scenarios

AbstractCoastal wetlands are large reservoirs of soil carbon (C). However, the annual C accumulation rates contributing to the C storage in these systems have yet to be spatially estimated on a large scale. We synthesized C accumulation rate (CAR) in tidal wetlands of the conterminous United States (US), upscaled the CAR to national scale, and predicted trends based on climate change scenarios. Here, we show that the mean CAR is 161.8 ± 6 g Cm−2 yr−1, and the conterminous US tidal wetlands sequestrate 4.2–5.0 Tg C yr−1. Relative sea level rise (RSLR) largely regulates the CAR. The tidal wetland CAR is projected to increase in this century and continue their C sequestration capacity in all climate change scenarios, suggesting a strong resilience to sea level rise. These results serve as a baseline assessment of C accumulation in tidal wetlands of US, and indicate a significant C sink throughout this century.

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