scholarly journals Intransitive atmosphere dynamics leading to persistent hot-dry or cold-wet European summers

2021 ◽  
pp. 1-48
Author(s):  
Ruud Sperna Weiland ◽  
Karin van der Wiel ◽  
Frank Selten ◽  
Dim Coumou
Keyword(s):  
Phase Space ◽  
Interannual Variability ◽  
Climate Model ◽  
Global Climate Model ◽  
Fundamental Property ◽  
Early Summer ◽  
Flow State ◽  
Climate Data ◽  
Initial State ◽  
Summer Circulation

AbstractPersistent hot-dry or cold-wet summer weather can have significant impacts on agriculture, health and the environment. For North-Western Europe, these weather regimes are typically linked to, respectively, blocked or zonal jetstream states. The fundamental dynamics underlying these circulation states are still poorly understood. Edward Lorenz postulated that summer circulation may be either fully or almost intransitive, implying that part of the phase space (capturing circulation variability) cannot be reached within one specific summer. If true, this would have major implications for the predictability of summer weather and our understanding of the drivers of interannual variability of summer weather. Here, we test the two Lorenz hypotheses (i.e. fully or almost intransitive) for European summer circulation, capitalising on a newly-available, very large ensemble (2000 years) of present-day climate data in the fully-coupled global climate model EC-Earth. Using Self-Organising Maps, we quantify the phase space of summer circulation and the trajectories through phase space in unprecedented detail. We show that, based on Markov assumptions, the summer circulation is strongly dependent on its initial state in early summer with the atmospheric memory ranging from 28 days up to ~45 days. The memory is particularly long if the initial state is either a blocked or a zonal flow state. Furthermore, we identify two groups of summers which are characterised by distinctly different trajectories through phase space, and which prefer either a blocked or zonal circulation state, respectively. These results suggest that intransitivity is indeed a fundamental property of the atmosphere and an important driver of interannual variability.

Global Instrumental Meteorological Database Before 1890 – a useful overview

2021 ◽  
Author(s):  
Elin Lundstad ◽  
Yuri Brugnera ◽  
Stefan Brönnimann
Keyword(s):  
Meteorological Parameters ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Meteorological Station ◽  
Climate Data ◽  
Data Set ◽  
Instrumental Data ◽  
The World ◽  
Climate Model Simulations

<p>This work describes the compilation of global instrumental climate data with a focus on the 18th and early 19th centuries. This database provides early instrumental data recovered for thousands of locations around the world. Instrumental meteorological measurements from periods prior to the start of national weather services are designated “early instrumental data”. Much of the data is taken from repositories we know (GHCN, ISTI, CRUTEM, Berkeley Earth, HISTALP). In addition, many of these stations have not been digitized before. Therefore,  we provide a new global collection of monthly averages of multivariable meteorological parameters before 1890 based on land-based meteorological station data. The product will be form as the most comprehensive global monthly climate data set, encompassing temperature, pressure, and precipitation as ever done. These data will be quality controlled and analyzed with respect to climate variability and they be assimilated into global climate model simulations to provide monthly global reconstructions. The collection has resulted in a completely new database that is uniform, where no interpolations are included. Therefore, we are left with climate reconstruction that becomes very authentic. This compilation will describe the procedure and various challenges we have encountered by creating a unified database that can later be used for e.g. models. It will also describe the strategy for quality control that has been adopted is a sequence of tests.</p>

scholarly journals Strong future increases in Arctic precipitation variability linked to poleward moisture transport

2020 ◽  
Author(s):  
Richard Bintanja ◽  
Karin van der Wiel ◽  
Eveline van der Linden ◽  
Jesse Reusen ◽  
Linda Bogerd ◽  
...  
Keyword(s):  
Interannual Variability ◽  
Moisture Transport ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Arctic Region ◽  
The Arctic ◽  
Climate Model Simulations ◽  
Mean Climate ◽  
Increasing Precipitation

<p>The Arctic region is projected to experience amplified warming as well as strongly increasing precipitation rates. Equally important to trends in the mean climate are changes in interannual variability, but changes in precipitation fluctuations are highly uncertain and the associated processes unknown. Here we use various state-of-the-art global climate model simulations to show that interannual variability of Arctic precipitation will likely increase markedly (up to 40% over the 21<sup>st</sup> century), especially in summer. This can be attributed to increased poleward atmospheric moisture transport variability associated with enhanced moisture content, possibly modulated by atmospheric dynamics. Because both the means and variability of Arctic precipitation will increase, years/seasons with excessive precipitation will occur more often, as will the associated impacts.</p>

scholarly journals Chaotic Statistical Downscaling (CSD): Application and Comparison in the Bogotá River Basin

10.29007/wkcx ◽  
2018 ◽  
Author(s):  
Freddy Duarte ◽  
Gerald Corzo ◽  
Germán Santos ◽  
Oscar Hernández
Keyword(s):  
Time Delay ◽  
Phase Space ◽  
Predictive Model ◽  
River Basin ◽  
Statistical Downscaling ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Deterministic Chaos ◽  
Climatic Information

This study presents a new statistical downscaling method called Chaotic Statistical Downscaling (CSD). The method is based on three main steps: Phase space reconstruction for different time steps, identification of deterministic chaos and a general synchronization predictive model. The Bogotá river basin was used to test the methodology. Two sources of climatic information are downscaled: the first corresponds to 47 rainfall gauges stations (1970-2016, daily) and the second is derived from the information of the global climate model MPI-ESM-MR with a resolution of 1,875° x 1,875° daily resolution. These time series were used to reconstruct the phase space using the Method of Time-Delay. The Time-Delay method allows us to find the appropriate values of the time delay and the embedding dimension to capture the dynamics of the attractor. This information was used to calculate the exponents of Lyapunov, which shows the existence of deterministic chaos. Subsequently, a predictive model is created based on the general synchronization of two dynamical systems. Finally, the results obtained are compared with other statistical downscaling models for the Bogota River basin using different measures of error which show that the proposed method is able to reproduce reliable rainfall values (RMSE=73.37).

scholarly journals Assessment of Impacts of Climate Change and Adaptation Measures for Maize Production in East Sikkim, India

2016 ◽  
Vol 9 (1) ◽  
pp. 15-27
Author(s):  
Proloy Deb ◽  
S. Babel
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Global Climate Model ◽  
Maize Yield ◽  
Future Climate ◽  
Yield Response ◽  
Climate Data ◽  
North East ◽  
The Impact ◽  
Impacts Of Climate Change

An investigation was carried out to assess the impacts of climate change on rainfed maize yield using a yield response to water stress model (AquaCrop) and to identify suitable adaptation options to minimize the negative impacts on maize yield in East Sikkim, North East India. Crop management and yield data was collected from the field experimental plots for calibration and validation of the model for the study area. The future climate data was developed for two IPCC emission scenarios A2 and B2 based on the global climate model HadCM3 with downscaling of climate to finer spatial resolution using the statistical downscaling model, SDSM. The impact study revealed that there is an expected reduction in maize yield of 12.8, 28.3 and 33.9% for the A2 scenario and 7.5, 19.9 and 29.9% for the B2 scenario during 2012-40, 2041-70 and 2071-99 respectively compared to the average yield simulated during the period of 1961-1990 with observed climate data. The maize yield of same variety under future climate can be maintained or improved from current level by changing planting dates, providing supplement irrigation and managing optimum nutrient.Journal of Hydrology and Meteorology, Vol. 9(1) 2015, p.15-27

scholarly journals Climate Data to Undertake Hygrothermal and Whole Building Simulations Under Projected Climate Change Influences for 11 Canadian Cities

Data ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. 72 ◽  
Author(s):  
Abhishek Gaur ◽  
Michael Lacasse ◽  
Marianne Armstrong
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Internal Variability ◽  
Climatic Conditions ◽  
Climate Data ◽  
Wide Range ◽  
The Future

Buildings and homes in Canada will be exposed to unprecedented climatic conditions in the future as a consequence of global climate change. To improve the climate resiliency of existing and new buildings, it is important to evaluate their performance over current and projected future climates. Hygrothermal and whole building simulation models, which are important tools for assessing performance, require continuous climate records at high temporal frequencies of a wide range of climate variables for input into the kinds of models that relate to solar radiation, cloud-cover, wind, humidity, rainfall, temperature, and snow-cover. In this study, climate data that can be used to assess the performance of building envelopes under current and projected future climates, concurrent with 2 °C and 3.5 °C increases in global temperatures, are generated for 11 major Canadian cities. The datasets capture the internal variability of the climate as they are comprised of 15 realizations of the future climate generated by dynamically downscaling future projections from the CanESM2 global climate model and thereafter bias-corrected with reference to observations. An assessment of the bias-corrected projections suggests, as a consequence of global warming, future increases in the temperatures and precipitation, and decreases in the snow-cover and wind-speed for all cities.

scholarly journals Interhemispheric effect of global geography on Earth's climate response to orbital forcing

2019 ◽  
Vol 15 (1) ◽  
pp. 377-388
Author(s):  
Rajarshi Roychowdhury ◽  
Robert DeConto
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Climate Response ◽  
Orbital Forcing ◽  
Climate Data ◽  
Unequal Distribution ◽  
Summer Temperatures ◽  
Earth’S Climate ◽  
Climate Responses

Abstract. The climate response of the Earth to orbital forcing shows a distinct hemispheric asymmetry due to the unequal distribution of land in the Northern Hemisphere versus Southern Hemisphere. This asymmetry is examined using a global climate model (GCM) for different climate responses such as mean summer temperatures and positive degree days. A land asymmetry effect (LAE) is quantified for each hemisphere and the results show how changes in obliquity and precession translate into variations in the calculated LAE. We find that the global climate response to specific past orbits is likely unique and modified by complex climate–ocean–cryosphere interactions that remain poorly known. Nonetheless, these results provide a baseline for interpreting contemporaneous proxy climate data spanning a broad range of latitudes, which may be useful in paleoclimate data–model comparisons, and individual time-continuous records exhibiting orbital cyclicity.

Building synergies in regional climate services for Southeast Asia: The ASEAN Regional Climate Data, Analysis and Projections (ARCDAP) workshop series.

2020 ◽  
Author(s):  
Gerald Lim ◽  
Aurel Moise ◽  
Raizan Rahmat ◽  
Bertrand Timbal
Keyword(s):  
Climate Change ◽  
Data Analysis ◽  
Southeast Asia ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Early Warning Systems ◽  
Climate Data ◽  
Climate Services

<p>Southeast Asia (SEA) is a rapidly developing and densely populated region that is home to over 600 million people. This, together with the region’s high sensitivity, exposure and low adaptive capacities, makes it particularly vulnerable to climate change and extremes such as floods, droughts and tropical cyclones. While the last decade saw some countries in SEA develop their own climate change projections, studies were largely uncoordinated and most countries still lack the capability to independently produce robust future climate information. Following a proposal from the World Meteorological Organisation (WMO) Regional Association (RA) V working group on climate services, the ASEAN Regional Climate Data, Analysis and Projections (ARCDAP) workshop series was conceived in 2017 to bridge these gaps in regional synergies. The ARCDAP series has been organised annually since 2018 by the ASEAN Specialised Meteorological Centre (hosted by Meteorological Service Singapore) with support from WMO through the Canada-funded Climate Risk and Early Warning Systems (Canada-CREWS) initiative.</p><p>This presentation will cover the activities and outcomes from the first two workshops, as well as the third which will be held in February 2020. The ARCDAP series has so far brought together representatives from ASEAN National Meteorological and Hydrological Services (NMHSs), climate scientists and end-users from policy-making and a variety of vulnerability and impact assessment (VIA) sectors, to discuss and identify best practices regarding the delivery of climate change information, data usage and management, advancing the science etc. Notable outputs include two comprehensive workshop reports and a significant regional contribution to the HadEX3 global land in-situ-based dataset of temperature and precipitation extremes, motivated by work done with the ClimPACT2 software.</p><p>The upcoming third workshop will endeavour to encourage the uptake of the latest ensemble of climate simulations from the Coupled Model Intercomparison Project (CMIP6) using CMIP-endorsed tools such as ESMValTool. This will address the need for ASEAN climate change practitioners to upgrade their knowledge of the latest global climate model database. It is anticipated that with continued support from WMO, the series will continue with the Fourth workshop targeting the assessment of downscaling experiments in 2021.</p>

scholarly journals Impacts of climate and catastrophic forest changes on streamflow and water balance in a mountainous headwater stream in Southern Alberta

2013 ◽  
Vol 17 (12) ◽  
pp. 4941-4956 ◽  
Author(s):  
V. Mahat ◽  
A. Anderson
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Similar Amount ◽  
Climate Change Scenarios ◽  
Climate Data ◽  
Stochastic Weather Generator ◽  
Precipitation Decrease ◽  
Southern Alberta

Abstract. Rivers in Southern Alberta are vulnerable to climate change because much of the river water originates as snow in the eastern slopes of the Rocky Mountains. Changes in likelihood of forest disturbance (wildfire, insects, logging, etc.) may also have impacts that are compounded by climate change. This study evaluates the impacts of climate and forest changes on streamflow in the upper parts of the Oldman River in Southern Alberta using a conceptual hydrological model, HBV-EC (Hydrologiska Byråns attenbalansavdelning, Environment Canada), in combination with a stochastic weather generator (LARS-WG) driven by GCM (global climate model) output climate data. Three climate change scenarios (A1B, A2 and B1) are selected to cover the range of possible future climate conditions (2020s, 2050s, and 2080s). The GCM projected less than a 10% increase in precipitation in winter and a similar amount of precipitation decrease in summer. These changes in projected precipitation resulted in up to a 200% (9.3 mm) increase in winter streamflow in February and up to a 63% (31.2 mm) decrease in summer flow in June. Flow also decreased in July and August, when irrigation is important; these reduced river flows during this season could impact agriculture production. The amplification in the streamflow is mostly driven by the projected increase in temperature that is predicted to melt winter snow earlier, resulting in lower water availability during the summer. Uncertainty analysis was completed using a guided GLUE (generalized likelihood uncertainty estimation) approach to obtain the best 100 parameter sets and associated ranges of streamflows. The impacts of uncertainty in streamflows were higher in spring and summer than in winter and fall. Forest change compounded the climate change impact by increasing the winter flow; however, it did not reduce the summer flow.

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