This is the personal website of scientist Dr. Jesse Dorrestijn.

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Contact

jesse at jessedorrestijn.nl

Position

At the moment, I give private mathematics lessons in Amsterdam. In the future, I hope to obtain a scientific position at a university or (governmental) institute.

Bio and CV

I am a Dutch scientist (and singer-songwriter). This is a link to my CV.

Interests

My scientific interests are mathematics - this is my background - and atmospheric sciences - the field in which I started working after my Master mathematics. For my PhD I studied the representation of atmospheric clouds and convection in weather and climate models - by using mathematical approaches, e.g. stochastic processes, data-driven methods.

The main motivation to do science is my interest in nature, Earth, the solar system, and the universe. Find out and understand how nature works.

I worked at the Center for Climate Sciences at the NASA Jet Propulsion Laboratory (JPL)/California Institute of Technology from November 2016 until November 2017. I was a Caltech Postdoctoral Scholar at JPL in the Atmospheric Physics and Weather group. I worked with satellite data of temperature and humidity / clouds with the goal of understanding more about atmospheric clouds to be able to improve the representations of clouds and convection in weather and climate models.
JPL

A list of topics that I like:

Atmosphere

Mathematics

(I'm not an expert in all these topics.)

Scientific Papers

A.P. Siebesma and J. Dorrestijn. New Pathways for Moist Convection Parameterisation. Current Trends in the Representation of Physical Processes in Weather and Climate Models, Springer, Singapore, 2019. 329-347. Springer, Singapore, 2019. 329-347.

J. Dorrestijn, B.H. Kahn, J. Teixeira and F.W. Irion. Instantaneous variance scaling of AIRS thermodynamic profiles using a circular area Monte Carlo approach, Atmos. Meas. Tech., 11, 2717-2733, 2018.

J. Dorrestijn, D.T. Crommelin, A.P. Siebesma, H.J.J. Jonker, and F. Selten. Stochastic convection parameterization with Markov chains in an intermediate complexity GCM. J. Atmos. Sci., 73:1367-1382, 2016.

J. Dorrestijn, D.T. Crommelin, A. Pier Siebesma, H.J.J. Jonker, and C. Jakob. Stochastic parameterization of convective area fractions with a multicloud model inferred from observational data. J. Atmos. Sci., 72:854-869, 2015.

J. Dorrestijn, D.T. Crommelin, J.A. Biello, and S.J. Böing. A data-driven multi-cloud model for stochastic parametrization of deep convection. Phil. Trans. R. Soc. A, 371:20120374, 2013.

J. Dorrestijn, D.T. Crommelin, A.P. Siebesma, and H.J.J. Jonker. Stochastic parameterization of shallow cumulus convection estimated from highresolution model data. Theor. Comput. Fluid Dyn., 27:133-148, 2013.

Posters

I made a poster about my PhD research. It won the best poster award at the Nederlands Mathematisch Congres 2011 at Twente University. This is a link to my first poster.

I made a second poster. I presented this poster at the AGU Fall Meeting in San Francisco at Friday 7 December 2012 Hall A-C of the Moscone South building in the session A53F Cloud and Multiscale Modeling of the Atmosphere. This is a link to my second poster.

My third poster made for the Probabilistic Cellular Automata (PCA) Workshop in Eindhoven 2013: This is a link to my third poster.

My fourth poster made for the GEWEX meeting in Den Haag 2014: This is a link to my fourth poster.


Master's thesis mathematics

The topic of my Master's thesis was Benford's Law. If one investigates numbers obtained from the most various sources, one sees to his surprise that in general the first digits do not follow the expected uniform distribution. The first digits tend to be distributed logarithmically. That means that thirty percent of numbers starts with the digit 1. This strange phenomenon was found by Simon Newcomb in 1881 and by Frank Benford in 1937. The fact that the first digits of random numbers of random distributions are distributed as predicted by Benford has been proved by Ted Hill in 1995. In the article in which the proof was published, Ted Hill posed another problem: what kind of probability distributions satisfy Benford's Law? In my thesis I defined and examined Benford's Law for an arbitrary real base. Data has been used to illustrate the developed theory. I contacted Ted Hill, who came twice to Utrecht to help me improving my thesis. I received a NWO research grant to pay for Ted Hill's expenses.

This is a link to my master's thesis.

Dissertation

For my PhD research I looked at the representations of convective clouds in weather and climate models. The aim was to improve the representation of these clouds by using a mathematical tool: Markov chains. Markov chains are stochastic processes that switch between a finite number of states with certain probabilities. By estimating these probabilities from data of convection, a realistic model could be constructed. Data of convection was first obtained from Large-Eddy Simulation and later from a rain radar in Darwin, Australia. The new Markov chain model was used in a climate model of intermediate complexity "SPEEDY", to serve as a closure for the cloud base mass flux. I examined precipitation patterns in the tropics and how the model changed these patterns.

-->Link to dissertation pdf file -->

Matlab files

Here you can find Matlab codes that are focused on data-driven Markov chains, that I used during my PhD research at CWI, Amsterdam.

-->This is a link to the Matlab code page<--

Links to Youtube movies:

A Cloud type movie, corresponding to the work of the Trans. R. Soc. A paper (see papers).

Stochastic cellular automata movie, also corresponding to the work of the Trans. R. Soc. A paper (see papers).

Conferences, workshops:

past events




Last update: Dec. 11th, 2019