Climate Modeling for Macroeconomic Policy: A Case Study for Pakistan

2021 ◽  
Author(s):  
Andrew Burns ◽  
Charl Jooste ◽  
Gregor Schwerhoff
Keyword(s):  
Climate Modeling ◽  
Macroeconomic Policy

scholarly journals Experiences with virtual schools on “Climate data for impact assessments”

2021 ◽  
Author(s):  
Janette Bessembinder ◽  
Judith Klostermann ◽  
Rutger Dankers ◽  
Vladimir Djurdjevic ◽  
Tomas Halenka
Keyword(s):  
Summer School ◽  
Climate Modeling ◽  
Virtual Schools ◽  
Virtual School ◽  
Climate Data ◽  
Climate Services ◽  
Impact Modelling ◽  
Set Up ◽  
Impact Models

<p>The provision of climate services to users is a fast developing field. In support of this development, the IS-ENES3 project, funded within the EC Horizon2020 program, organized three schools on “Climate data for impact assessments” in 2020 and 2021. In an Autumn school, a Spring school and a Summer school, climate scientists and impact scientists were brought together. An important aim of the schools was to enhance interaction between Vulnerability-Impact-Adaptation (VIA) researchers, climate services providers and climate researchers. Another aim was to provide an overview of information on climate modeling, climate data, impact modelling and climate services based on the work of the IS-ENE3 project.</p><p>In the first three weeks a series of lectures was given, covering topics such as climate data and modelling, impact models, portals for accessing and processing climate data, setting-up impact assessments, and communication of results to stakeholders. In the last three weeks the participants worked in small groups of one climate scientist with one impact scientist on a case study under the guidance of the course lecturers. Impact and climate researchers were combined on purpose to let them experience how they could help each other.</p><p>Originally the schools were planned to take place on-site (e.g. in Prague) during one week; however, due to COVID-19 the schools had to be transformed to virtual schools with two weekly sessions during six weeks. Although the virtual set-up had some disadvantages (e.g. less possibilities for networking), there were also some advantages (e.g. the possibility to record the lectures and make them available to a broader audience; more time to explore and work with climate data in between the sessions, no CO<sub>2</sub> emissions for travelling). During this presentation we will present the set-up of the schools and the conversion to a virtual school. We will focus on the lessons learnt and the evaluation of the virtual schools by the participants and give some recommendations for similar schools and how to link the climate and VIA research communities .</p>

Epidemic waves in relief against a structured climatic background

2021 ◽  
Author(s):  
Peter Carl
Keyword(s):  
Climate Modeling ◽  
Sunshine Duration ◽  
Climate Data ◽  
Data Set ◽  
Seir Model ◽  
Epidemic Curve ◽  
Surface Climate ◽  
Spatially Distributed

<p>For directly transmissible infectious diseases, seasonality in the course of epidemics may manifest in four major ways: susceptibility of the hosts, their individual and collective behavior, transmissibility of the pathogen, and survival of the latter under evolving environmental conditions. Mechanisms and concepts are not finally settled, notably in a pandemic setting. Climatic seasonality by itself is an aggregate, structured phenomenon that provides a spatially distributed background to the epidemic outbreak and its evolution at multiple timescales. Using advanced methods of data and systems analysis, including epidemiological and climate modeling, the RKI data of the COVID-19 epidemic curve for Berlin and a five-parameter climate data set of the nearby station Lindenberg (Mark) are analyzed in daily resolution over the period March 2020 to October 2021. Aimed to identify extrinsic impacts due to organized intraseasonal climate dynamics, as seen in sunshine duration and surface climate (pressure, temperature, humidity, wind), on intrinsic dynamics of the epidemic system, an established (SEIR) model of the latter and modifications thereof have been subjected to in-depth studies with a view on both genesis and timing of epidemic waves and their potential synchronization with climatic background dynamics. Starting with a case study for the spring 2020 period of shutdown, which unveils remarkable synchronies with the seasonal transition, estimates are given and applied to the follow-up period of individual and combined impacts of climate variables on the SEIR model in different oscillatory (non-equilibrium, lately endemic) regimes of operation.</p>

Social Learning and Macroeconomic Policy in Britain

2001 ◽  
Vol 21 (2) ◽  
pp. 133-152 ◽  
Author(s):  
IAN GREENER
Keyword(s):  
Social Learning ◽  
Policy Change ◽  
Policy Instruments ◽  
Macroeconomic Policy ◽  
Social Constructionist ◽  
Learning Models ◽  
The Social ◽  
Constructionist Approach ◽  
The 1960S

This paper examines the social learning models of policy of Hall and May attempting to create a synthesis of the best elements of each. We then apply the revised model to three specific instances of macroeconomic policy in Britain; the introduction of ‘Keynesian-plus’ policy in the 1960s, the movement from Keynesianism to monetarism, and the experiment with monetarism in the 1980s. In each case study, the degree of policy change is assessed, and possible reasons for that level of change explored. We conclude that a more social constructionist approach is required to understand the link between policy instruments, indicators, and paradigms, and, alongside this, a greater need to understand the implications of the assumptions underlying policy.

The Hydroarchaeological Method: A Case Study at the Maya Site of Palenque

2012 ◽  
Vol 23 (1) ◽  
pp. 29-50 ◽  
Author(s):  
Kirk D. French ◽  
Christopher J. Duffy ◽  
Gopal Bhatt
Keyword(s):  
Climate Changes ◽  
Water Cycle ◽  
Climate Modeling ◽  
Regional Climate ◽  
Water System ◽  
Archaeological Site ◽  
Convincing Evidence ◽  
Watershed Land Use ◽  
Maya Site

AbstractThis research consists mainly of introducing the hydroarchaeological method, especially as related to issues of drought. The article outlines how this multidisciplinary method can provide insights into the success and failures of an archaeological site, in this case the Maya site of Palenque. We also detail convincing evidence that shows that the Maya of Palenque did not leave their city because of deficiencies of water, as some paleoclimatologists and archaeologists have asserted. The first logical step toward understanding any settlement’s water system is to use basic hydrologic methods and theory and to understand the local watershed. There is great potential for watershed-climate modeling in developing plausible scenarios of water use and supply and of the effect of extreme conditions (flood and drought), all of which cannot be fully represented by atmosphere-based climate and weather projections. The research demonstrates how the local watershed, land-use, and ecological conditions interact with regional climate changes. The archaeological implications for this noninvasive “virtual” method are many, including detecting periods of stress within a community, estimating population by developing caps based on the availability of water, and understanding settlement patterns, as well as assisting present local populations in understanding their water cycle.

scholarly journals Assessing local daily temperatures by means of novel analog approaches: a case study based on the city of Augsburg, Germany

2021 ◽  
Author(s):  
Christian Merkenschlager ◽  
Stephanie Koller ◽  
Christoph Beck ◽  
Elke Hertig
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Climate Modeling ◽  
Selection Process ◽  
Urban Climate ◽  
Domain Size ◽  
Normal Vector ◽  
Circulation Patterns ◽  
The City

AbstractWithin the scope of urban climate modeling, weather analogs are used to downscale large-scale reanalysis-based information to station time series. Two novel approaches of weather analogs are introduced which allow a day-by-day comparison with observations within the validation period and which are easily adaptable to future periods for projections. Both methods affect the first level of analogy which is usually based on selection of circulation patterns. First, the time series were bias corrected and detrended before subsamples were determined for each specific day of interest. Subsequently, the normal vector of the standardized regression planes (NVEC) or the center of gravity (COG) of the normalized absolute circulation patterns was used to determine a point within an artificial coordinate system for each day. The day(s) which exhibit(s) the least absolute distance(s) between the artificial points of the day of interest and the days of the subsample is/are used as analog or subsample for the second level of analogy, respectively. Here, the second level of analogy is a second selection process based on the comparison of gridded temperature data between the analog subsample and the day of interest. After the analog selection process, the trends of the observation were added to the analog time series. With respect to air temperature and the exceedance of the 90th temperature quantile, the present study compares the performance of both analog methods with an already existing analog method and a multiple linear regression. Results show that both novel analog approaches can keep up with existing methods. One shortcoming of the methods presented here is that they are limited to local or small regional applications. In contrast, less pre-processing and the small domain size of the circulation patterns lead to low computational costs.

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