Quantification of the relation between dynamical properties of meteorological variables and their predictability

Local properties of chaotic systems can be summarized by dynamical indicators, that describe the recurrences of all states in phase space. Faranda et al. (2017) defined such indicators with the local dimension (d, approximating the local number of degrees of freedom of the system) and the inverse of persistence (&#952;, approximating the time it takes to leave a local state). It has been conjectured that such indicators give access to the local predictability of systems. The aim of this study is to evaluate how the predictability of climate variables such as temperature and precipitation is related to dynamical properties of the atmospheric flow.The predictability of a chaotic system can be evaluated through ensembles of simulations, with probability scores (e.g. Continuous Rank Probability Score, CRPS). In this work, we consider ensembles of climate forecasts with a stochastic weather generator (SWG) based on analogs of atmospheric circulation (Yiou and D&#233;andr&#233;is, 2019). We are interested in relating predictability scores of European temperatures and precipitation, obtained with this SWG, and the local dynamical properties of the synoptic atmospheric circulation, obtained from the NCEP reanalysis. We show experimentally that the CRPS of local climate variables can be predicted from large-scale (d, \ &#952;) values of geopotential height fields, for time leads of 5 to 10 days. A practical application is that the predictability of local variables (in Europe) can be anticipated from large-scale dynamical quantities, which can help to dimension the size of ensemble forecasts.ReferencesFaranda, D., Messori, G., Yiou, P., 2017. Dynamical proxies of North Atlantic predictability and extremes. Sci. Rep. 7, 41278. https://doi.org/10.1038/srep41278Caby, T. Extreme Value Theory for dynamical systems, with applications in climate and neuroscience. Mathematics [math]. Universit&#233; de Toulon Sud; Universita dell&#8217;Insubria, 2019. English.tel-02473235v1Yiou, P., D&#233;andr&#233;is, C., 2019. Stochastic ensemble climate forecast with an analogue model. Geosci. Model Dev. 12, 723&#8211;734. https://doi.org/10.5194/gmd-12-723-2019&#160;AcknowledgmentsThis project has received funding from the European Union&#8217;s Horizon 2020 research and innovation programme under the Marie Sk&#322;odowska-Curie grant agreement No 813844.&#160;

Download Full-text

Ensemble weather forecast of precipitation with a stochastic weather generator based on analogues circulation

10.5194/egusphere-egu2020-4705 ◽

2020 ◽

Author(s):

Meriem Krouma ◽

Pascal Yiou ◽

Céline Déandréis ◽

Soulivanh Thao

Keyword(s):

Model Development ◽

Weather Generator ◽

Lead Times ◽

The European Union ◽

Ensemble Forecasts ◽

Analogue Model ◽

Data Set ◽

Stochastic Weather Generator ◽

Horizon 2020 ◽

Skill Scores

AbstractThe aim of this study is to assess the skills of a stochastic weather generator (SWG) to forecast precipitation in Europe. The SWG is based on the random sampling of circulation analogues, which is a simple form of machine learning simulation. The SWG was developed and tested by Yiou and D&#233;andr&#233;is (2019) to forecast daily average temperature and the NAO index. Ensemble forecasts with lead times from 5 to 80 days were evaluated with CRPSS scores against climatology and persistence forecasts. Reasonable scores were obtained up to 20 days. &#160;In this study, we adapt the parameters of the analogue SWG to optimize the simulation of European precipitations. We then analyze the performance of this SWG for lead times of 2 to 20 days, with the forecast skill scores used by Yiou and D&#233;andr&#233;is (2019). To achieve this objective, the SWG will use ECA&D precipitation data (Haylock. 2002), and the analogues of circulation will be computed from sea-level pressure (SLP) or geopotential heights (Z500) from the NCEP reanalysis. This provides 100-member ensemble forecasts on a daily time increment. We will evaluate the seasonal dependence of the forecast skills of precipitation and the conditional dependence to weather regimes. Comparisons with &#8220;real&#8221; medium range forecasts from the ECMWF will be performed.ReferencesYiou, P., and C&#233;line D.. Stochastic ensemble climate forecast with an analogue model. Geoscientific Model Development 12, 2 (2019): 723&#8209;34.Haylock, M. R. et al.. A European daily high-resolution gridded data set of surface temperature and precipitation for 1950-2006. J. Geophys. Res. - Atmospheres 113, D20 (2008): doi:10.1029/2008JD010201.&#160;AcknowledgeThis project has received funding from the European Union&#8217;s Horizon 2020 research and innovation programme under the Marie Sk&#322;odowska-Curie grant agreement No 813844.

Download Full-text

Estimation of soil moisture content using Citizen observatory data -lessons learnt from GROW Observatory project

10.5194/egusphere-egu2020-7613 ◽

2020 ◽

Author(s):

Endre Dobos ◽

Károly Kovács ◽

Daniel Kibirige ◽

Péter Vadnai

Keyword(s):

Soil Moisture ◽

Monitoring System ◽

Large Scale ◽

Technological Development ◽

Special Focus ◽

Agricultural Activity ◽

The European Union ◽

Horizon 2020 ◽

Soil Moisture Monitoring

Soil moisture is a crucial factor for agricultural activity, but also an important factor for weather forecast and climate science. Despite of the technological development in soil moisture sensing, no full coverage global or continental or even national scale soil moisture monitoring system exist.&#160; There is a new European initiative to demonstrate the feasibility of a citizen observatory based soil moisture monitoring system.&#160; The aim of this study is to characterize this new monitoring approach and provide provisional results on the interpretation and system performance.GROW Observatory is a project funded under the European Union&#8217;s Horizon 2020 research and innovation program. Its aim is to establish a large scale (>20,000 participants), resilient and integrated &#8216;Citizen Observatory&#8217; (CO) and community for environmental monitoring that is self-sustaining beyond the life of the project. This article describes how the initial framework and tools were developed to evolve, bring together and train such a community; raising interest, engaging participants, and educating to support reliable observations, measurements and documentation, and considerations with a special focus on the reliability of the resulting dataset for scientific purposes. The scientific purposes of GROW observatory are to test the data quality and the spatial representativity of a citizen engagement driven spatial distribution as reliably inputs for soil moisture monitoring and&#160;&#160; to create timely series of&#160; gridded soil moisture products based on citizens&#8217; observations using low cost soil moisture (SM) sensors, and to provide an extensive dataset of in-situ soil moisture observations which can serve as a reference to validate satellite-based SM products and support the Copernicus in-situ component. This article aims to showcase the design, tools and the digital soil mapping approaches of the final soil moisture product.

Download Full-text

Eddy statistics validation of an ORCA12 ocean and sea ice model for the Arctic with satellite data

10.5194/egusphere-egu2020-8445 ◽

2020 ◽

Author(s):

Stefanie Rynders ◽

Yevgeny Akesenov ◽

Igor Kozlov

Keyword(s):

Sea Ice ◽

Arctic Ocean ◽

Large Scale ◽

Mixed Layer Depth ◽

Three Dimensional ◽

The Arctic ◽

The European Union ◽

Boundary Current ◽

Horizon 2020 ◽

The Uk

As sea ice and ocean models are moving to higher resolution it becomes possible to permit eddy formation even in the Arctic Ocean. Eddies can affect the three dimensional ocean state through causing mixing and even ventilation of subsurface ocean layers if they are deep enough. To ensure models have the potential to simulate the density structure correctly it is therefore necessary to start doing model validation of not only the large scale ocean state, but also of the eddy field. Eddy statistics for the Arctic are available from satellite for the Western Arctic Ocean and the Fram Strait, in particular on number, size and cyclonicity of eddies for open ocean versus ice covered sites. These are compared to a NEMO-LIM 1/12 degree sea ice and ocean simulation (resolution 2-5km), upon which the model based statistics are expanded to the whole Arctic. In the model it is also possible to examine the depth structure of eddies, allowing to generate size vs. depth statistics. This, together with climatological mixed layer depth, provides a first estimate to get satellite-based information on mixing from eddies in the Arctic. We also map the maximum depth of eddies, to examine ventilation and identify sites with especially deep eddies, for instance at the boundary current. Acknowledgements: Grant NE/R000654/1 &#8220;Towards a Marginal Sea Ice Cover&#8221; funded by the UK Natural Research Council (NERC) and the UK-Russia Arctic bursaries program funded by the United Kingdom&#8217;s Department for Business, Energy and Industrial Strategy. The study is also supported from the project &#8220;The Advective Pathways of nutrients and key Ecological substances in the Arctic (APEAR)&#8221; (grant NE/R012865/1) funded by the Joint UK NERC/German Federal Ministry of Education and Research Changing Arctic Ocean Programme. This project has received funding from the European Union&#8217;s Horizon 2020 research and innovation programme under grant agreement No 821926 (IMMERSE). IK acknowledges the support from RFBR grant No 18-35-20078.

Download Full-text

Climate Advanced Forecasting of sub-seasonal Extremes (CAFE), ITN Project

10.5194/egusphere-egu2020-8907 ◽

2020 ◽

Author(s):

Alvaro Corral ◽

Keyword(s):

Large Scale ◽

Early Stage ◽

Climate Science ◽

Extreme Weather ◽

Extreme Weather Events ◽

The European Union ◽

Atmospheric Flow ◽

Horizon 2020 ◽

Research And Innovation ◽

Seasonal Time Scale

The CAFE Project is a Marie S. Curie Innovative-Training-Network (ITN) project funded by the EU. The ultimate goal of the CAFE project is to contribute to the improvement of sub-seasonal predictability of extreme weather events. This will be addressed through a structured and cross-disciplinary program, training 12 early stage researchers who undertake their PhD theses. CAFE brings together a team of co-supervisors with complementary expertise in climate science, meteorology, statistics and nonlinear physics.The CAFE team comprises ten beneficiaries (seven academic centres, one governmental agency, one intergovernmental agency and one company: ARIA, CRM, CSIC, ECMWF, MeteoFrance, MPIPKS, PIK, TUBAF, UPC, UR) and ten partner organizations (CEA and Munich Re, among them).CAFE research is organized into three main lines: Atmospheric and oceanic processes, Analysis of extremes, and Tools for predictability, all focused on the sub-seasonal time scale. This includes the study of Rossby wave packets, Madden-Julian oscillation, Lagrangian coherent structures, ENSO-related extreme weather anomalies, cascades of extreme events, extreme precipitation, large-scale atmospheric flow patterns, and stochastic weather generators, among other topics.Information about the CAFE project will be updated at:http://www.cafes2se-itn.eu/https://twitter.com/CAFE_S2SExtremThis project receives funding from the European Union&#8217;s Horizon 2020 research and innovation programme under the Marie Sk&#322;odowska-Curie grant agreement No 813844.

Download Full-text

Can local climate variability be explained by weather patterns? A multi-station evaluation for the Rhine basin

10.5194/hess-2016-286 ◽

2016 ◽

Author(s):

Aline Murawski ◽

Gerd Bürger ◽

Sergiy Vorogushyn ◽

Bruno Merz

Keyword(s):

Climate Variability ◽

General Circulation ◽

Large Scale ◽

Synoptic Situation ◽

Stochastic Weather Generator ◽

Local Climate ◽

Weather Patterns ◽

Rhine Basin ◽

Weather Pattern ◽

Temperature And Humidity

Abstract. For understanding past flood changes in the Rhine catchment and in particular for quantifying the role of anthropogenic climate change for extreme flows, an attribution study relying on a proper GCM (General Circulation Model) downscaling is needed. A downscaling based on conditioning a stochastic weather generator on weather patterns is a promising approach given, among others, a strong link between weather patterns and local climate, and sufficient GCM skill in reproducing weather pattern climatology. To test the first requirement, an objective classification scheme is applied and different classification variables, spatial domains and number of classes are evaluated. To this end, 111 years of daily climate data from 500 stations in the Rhine basin are used. A classification based on a combination of mean sea level pressure, temperature, and humidity from the ERA20C reanalysis for a relatively small spatial domain over Central Europe with overall 40 weather type classes is found most appropriate for stratifying six local climate variables. The skill in explaining local climate variability is very different, from high for radiation to low for precipitation. Especially local precipitation and humidity are governed by processes that are not completely represented by the large-scale distribution of pressure, temperature and humidity. Before applying the weather pattern based downscaling approach, it should therefore be investigated whether the link between the large-scale synoptic situation and the local climate variable of interest is strong enough for the given purpose. Our analysis suggests that it is advantageous to incorporate additional classification variables besides pressure fields. The use of temperature results in a very good stratification of weather patterns throughout the year. Hence, there is no need to provide different classifications for each season. To test the skill of the latest generation of GCMs in reproducing the frequency, seasonality, and persistence of the derived weather patterns, output from 15 GCMs from the CMIP5 ensemble is evaluated. Most GCMs are able to capture these characteristics well, but some models showed consistent deviations in all three evaluation criteria and should be excluded from further attribution analysis.

Download Full-text

Long-Term Lake Area Change and Its Relationship with Climate in the Endorheic Basins of the Tibetan Plateau

Remote Sensing ◽

10.3390/rs13245125 ◽

2021 ◽

Vol 13 (24) ◽

pp. 5125

Author(s):

Junxiao Wang ◽

Mengyao Li ◽

Liuming Wang ◽

Jiangfeng She ◽

Liping Zhu ◽

...

Keyword(s):

Tibetan Plateau ◽

Large Scale ◽

Driving Forces ◽

Atlantic Multidecadal Oscillation ◽

The Tibetan Plateau ◽

Lake Area ◽

Climate Variables ◽

Landsat Images ◽

Area Change ◽

Local Climate

Lakes are sensitive indicators of climate change in the Tibetan Plateau (TP), which have shown high temporal and spatial variability in recent decades. The driving forces for the change are still not entirely clear. This study examined the area change of the lakes greater than 1 km2 in the endorheic basins of the Tibetan Plateau (EBTP) using Landsat images from 1990 to 2019, and analysed the relationships between lake area and local and large-scale climate variables at different geographic scales. The results show that lake area in the EBTP has increased significantly from 1990 to 2019 at a rate of 432.52 km2·year−1. In the past 30 years, lake area changes in the EBTP have mainly been affected by local climate variables such as precipitation and temperature. At a large scale, Indian Summer Monsoon (ISM) has correlations with lake area in western sub-regions in the Inner Basin (IB). While Atlantic Multidecadal Oscillation (AMO) has a significant connection with lake area, the North Atlantic Oscillation (NAO) does not. We also found that abnormal drought (rainfall) brought by the El Niño/La Niña events are significantly correlated with the lake area change in most sub-regions in the IB.

Download Full-text

Influence of atmospheric circulation on glacier mass balance in western Tibet: an analysis based on observations and modeling

Journal of Climate ◽

10.1175/jcli-d-20-0988.1 ◽

2021 ◽

pp. 1-55

Author(s):

Meilin Zhu ◽

Lonnie G. Thompson ◽

Huabiao Zhao ◽

Tandong Yao ◽

Wei Yang ◽

...

Keyword(s):

Mass Balance ◽

Atmospheric Circulation ◽

Air Temperature ◽

Large Scale ◽

Snow Accumulation ◽

Balance Model ◽

Glacier Mass Balance ◽

The Tibetan Plateau ◽

Local Climate ◽

Average Mass

AbstractGlacier changes on the Tibetan Plateau (TP) have been spatially heterogeneous in recent decades. The understanding of glacier mass changes in western Tibet, a transitional area between the monsoon-dominated region and the westerlies-dominated region, is still incomplete. For this study, we used an energy-mass balance model to reconstruct annual mass balances from October 1967 to September 2019 to explore the effects of local climate and large-scale atmospheric circulation on glacier mass changes in western Tibet. The results showed Xiao Anglong Glacier is close to a balanced condition, with an average value of -53±185 mm w.e. a-1 for 1968-2019. The interannual mass balance variability during 1968-2019 was primary driven by ablation-season precipitation, which determined changes in the snow accumulation and strongly influenced melt processes. The interannual mass balance variability during 1968-2019 was less affected by ablation-season air temperature, which only weakly affected snowfall and melt energy. Further analysis suggests that the southward (or northward) shift of the westerlies caused low (or high) ablation-season precipitation, and therefore low (or high) annual mass balance for glaciers in western Tibet. In addition, the average mass balance for Xiao Anglong Glacier was 83±185, -210±185, and -10±185 mm w.e. a-1 for 1968-1990, 1991-2012, and 2013-2019, respectively. These mass changes were associated with the variations in precipitation and air temperature during the ablation season on interdecadal time scales.

Download Full-text

Vertical interval dynamics of greenhouse gases in groundwater (Hesbaye chalk aquifer, Belgium)

10.5194/egusphere-egu2020-4958 ◽

2020 ◽

Author(s):

Olha Nikolenko ◽

Cedric Morana ◽

Bernard Taminiau ◽

Alberto V. Borges ◽

Tanguy Robert ◽

...

Keyword(s):

Greenhouse Gases ◽

Large Scale ◽

Stratospheric Ozone ◽

Sampling Technique ◽

Low Flow ◽

The European Union ◽

Horizon 2020 ◽

Research And Innovation ◽

Chalk Aquifer ◽

Insight Into

Increase in the concentration of greenhouse gases (GHGs) in the atmosphere threatens the existence of many ecosystems and their inhabitants. Agricultural activities contribute up to 70 % of total anthropogenic emission of nitrous oxide (N2O), one of the GHGs, which is characterized with the highest global warming potential and contributes to stratospheric ozone depletion. Our study presents the results obtained from the recent field and lab activities carried out in order to obtain better insight into the factors that define the presence of N2O in groundwater. Previous large scale investigations, performed in the Hesbaye chalk aquifer in Eastern Belgium, suggested that the concentration of N2O in the aquifer depends on different, possibly overlapping biochemical processes such as nitrification, denitrification and/or nitrifier-denitrification. This study explored the occurrence of biochemical stratification in the same aquifer and its impact on N2O production and consumption mechanisms. For this purpose low flow sampling technique was applied at different depth intervals to obtain better insight into the extent of oxic and anoxic zones and variability of concentrations of GHGs along the vertical profile. Collected groundwater samples were analyzed for the range of hydrochemical parameters as well as NO3-, N2O, H2O and B isotopes signatures and N2O isotopomers. Afterwards, rates of nitrification and denitrification processes were estimated based on short-term incubations of collected groundwater amended with NO3- and NH4+ compounds labeled with heavy 15N isotope. In addition, in order to characterize the dynamics of ongoing biogeochemical processes, polymerase chain reaction (PCR) tests for detection of the activity-specific enzymes in the aquifer were performed. Such studies help to clarify which conditions are more prone to the accumulation of high concentrations of GHGs in aquifers and better constrain models which estimate local and regional GHGs budgets.AcknowledgmentsThis project has received funding from the European Union&#8217;s Horizon 2020 research and innovation&#160; programme under the Marie Sk&#322;odowska-Curie grant agreement No 675120.

Download Full-text

A Comprehensive Analysis of Public and Private Funding for Photovoltaics Research and Development in the European Union, Norway, and Turkey

Energies ◽

10.3390/en13112743 ◽

2020 ◽

Vol 13 (11) ◽

pp. 2743 ◽

Cited By ~ 1

Author(s):

Juan Francisco De Negri ◽

Simon Pezzutto ◽

Sonia Gantioler ◽

David Moser ◽

Wolfram Sparber

Keyword(s):

European Union ◽

Research And Development ◽

Large Scale ◽

Private Investment ◽

The European Union ◽

Private Funding ◽

Member States ◽

Horizon 2020 ◽

European Investment ◽

National Budgets

This study aimed to examine the financing of photovoltaics research and development by analyzing funding from public (European Union and national budgets) and private sources (enterprises), Strategic Energy Technology Plan participating countries being the main focus (European Union Member States plus Norway and Turkey). In the coming years, photovoltaics are expected to heavily contribute towards the achievement of audacious climate and energy objectives. Continuous monitoring of the effects is of great importance to assess a course of action taken at such a large scale. It will be revealed that the distribution of funding provided by national budgets highly concentrates on a few Member States, which is part of a general trend in Research and Development within Europe. Approximately 85% of the current European investment provided by the EU budget is administered in the framework of the Horizon 2020 (2014–2020) program; private investment behaves differently. The European photovoltaics manufacturing market has been obliterated by low-budget imported goods. A major characteristic is that the remaining companies are almost exclusively privately held. Gathering data has consequently been a challenge, as opposed to the readily available public datasets.

Download Full-text

Changing correlation structures of the Northern Hemisphere atmospheric circulation from 1000 to 2100 AD

Climate of the Past Discussions ◽

10.5194/cpd-9-4987-2013 ◽

2013 ◽

Vol 9 (4) ◽

pp. 4987-5018 ◽

Cited By ~ 1

Author(s):

C. C. Raible ◽

F. Lehner ◽

J. F. Gonzalez Rouco ◽

L. Fernandez Donado

Keyword(s):

Atmospheric Circulation ◽

Northern Hemisphere ◽

Spatial Patterns ◽

Large Scale ◽

Eastern Mediterranean ◽

Wave Train ◽

Coupled Models ◽

Western Atlantic ◽

Local Climate ◽

Dipole Pattern

Abstract. Atmospheric circulation modes are important concepts to understand the variability of atmospheric dynamics. Assuming their spatial patterns to be fixed, such modes are often described by simple indices derived from rather short observational data sets. The increasing length of reanalysis products allows scrutinizing these concepts and assumptions. Here we investigate the stability of spatial patterns of Northern Hemisphere teleconnections by using the Twentieth Century Reanalysis as well as several control and transient millennium-scale simulations with coupled models. The observed and simulated centers of action of the two major teleconnection patterns, the North Atlantic Oscillation (NAO) and to some extent the Pacific North American (PNA), are not stable in time. The currently observed dipole pattern of the NAO with its center of action over Iceland and the Azores split into a North-South dipole pattern in the western Atlantic and a wave train pattern in the eastern part connecting the British Isles with West Greenland and the Eastern Mediterranean in the period 1940–1969 AD. The PNA centers of action over Canada are shifted southwards and over Florida into the Gulf of Mexico in the period 1915–1944 AD. The analysis further shows that shifts in the centers of action of either telconnection pattern are not related to changes in the external forcing applied in transient simulations of the last millennium. Such shifts in their centers of action are associated with changes in the relation of local precipitation and temperature to the overlying atmospheric mode. These findings further undermine the assumption of stationarity between local climate/proxy variability and large-scale dynamics inherent in proxy-based reconstructions of atmospheric modes and call for a more robust understanding of atmospheric variability on decadal time scales.

Download Full-text