Reproducible simulations with Singularity

This article was originally posted on the author’s personal blog.

Reproducing the result of a scientific experiment is necessary to establish trust, and reproducibility has long been a key part of the scientific method. Traditionally, an experiment could be repeated by following the method documented by the original scientists: setting up apparatus, taking measurements, and so on. If the method was sufficiently well documented then it was, perhaps, likely that the original results could be reproduced. These ‘wet lab’ experiments continue today, but many experiments are now performed entirely on computers. Such computational experiments involve no physical apparatus, but merely the processing of input data files through some scientific software before writing more data files for later analysis and plotting.

Repeating computational experiments is particularly difficult because, before any results can be obtained, there are many pieces of software apparatus that must be assembled: we must install an operating system, choose the correct version of our programming language and all the necessary scientific libraries, and we must use input parameters that are identical to those used in the original experiment. Assembling any of these pieces incorrectly might lead to subtly incorrect results, obviously incorrect results, or a failure to obtain any results at all. All this places a burden on the original scientists to document every piece of software, its version number and input parameters, and places a burden on the scientist wishing to reproduce the results.

There are a variety of tools that help to relieve this burden by automating the process of conducting computational experiments. Singularity is one such tool, having been purpose-built for automating computational experiments. A scientist creates a single configuration file that provides all the information Singularity needs to assemble the pieces of software apparatus and perform the experiment. This way, instead of writing a ‘method’ section that is only human-readable, the scientist has written a configuration file that is both human-readable and machine-readable. Using this configuration, Singularity will create an image file with all the correct versions of scientific software pre-installed. The scientist can verify their work by reproducing their experiment themselves, and they can run the same experiment just by copying the image file between their personal laptop, office workstation, or their institution’s HPC cluster. And they can send their Singularity configuration file and image files to other scientists, or they can obtain a DOI by uploading the files to Zenodo, making their computational experiments citeable in the same way as their journal publications.

I’ve used Singularity to run my own atmospheric simulations using the OpenFOAM computational fluid dynamics software. While my results have yet to be reproduced by others, I regularly use Singularity to reproduce my own results on my laptop, university desktop and AWS cloud compute servers, giving me confidence that my software and my results are robust. Whenever I’ve been stuck, the friendly Singularity developers have been quick to help out on twitter. But overall, I’ve found Singularity to be easy to use, and anyone that is familiar with git commands should feel right at home using it. Give it a try!

Trouble in paradise: Climate change, extreme weather and wildlife conservation on a tropical island.

Joseph Taylor, NERC SCEARNIO DTP student. Zoological Society of London.

Email: J.Taylor5@pgr.reading.ac.uk

Projecting the impacts of climate change on biodiversity is important for informing

Mauritius Kestrel by Joe Taylor
Male Mauritius kestrel (Falco punctatus) in the Bambous Mountains, eastern Mauritius. Photo by Joe Taylor.

mitigation and adaptation strategies. There are many studies that project climate change impacts on biodiversity; however, changes in the occurrence of extreme weather events are often omitted, usually because of insufficient understanding of their ecological impacts. Yet, changes in the frequency and intensity of extreme weather events may pose a greater threat to ecosystems than changes in average weather regimes (Jentsch and Beierkuhnlein 2008). Island species are expected to be particularly vulnerable to climate change pressures, owing to their inherently limited distribution, population size and genetic diversity, and because of existing impacts from human activities, including habitat destruction and the introduction of non-native species (e.g. Fordham and Brook 2010).

Mauritius is an icon both of species extinction and the successful recovery of threatened species. However, the achievements made through dedicated conservation work and the investment of substantial resources may be jeopardised by future climate change. Conservation programmes in Mauritius have involved the collection of extensive data on individual animals, creating detailed longitudinal datasets. These provide the opportunity to conduct in-depth analyses into the factors that drive population trends.

My study focuses on the demographic impacts of weather conditions, including extreme events, on three globally threatened bird species that are endemic to Mauritius. I extended previous research into weather impacts on the Mauritius kestrel (Falco punctatus), and applied similar methods to the echo parakeet (Psittacula eques) and Mauritius fody (Foudia rubra). The kestrel and parakeet were both nearly lost entirely in the 1970s and 1980s respectively, having suffered severe population bottlenecks, but all three species have benefitted from successful recovery programmes. I analysed breeding success using generalised linear mixed models and analysed survival probability using capture-mark-recapture models. Established weather indices were adapted for use in this study, including indices to quantify extreme rainfall, droughts and tropical cyclone activity. Trends in weather indices at key conservation sites were also analysed.

The results for the Mauritius kestrel add to a body of evidence showing that precipitation is an important limiting factor in its demography and population dynamics. The focal population in the Bambous Mountains of eastern Mauritius occupies an area in which rainfall is increasing. This trend could have implications for the population, as my analyses provide evidence that heavy rainfall during the brood phase of nests reduces breeding success, and that prolonged spells of rain in the cyclone season negatively impact the survival of juveniles. This probably occurs through reductions in hunting efficiency, time available for hunting and prey availability, so that kestrels are unable to capture enough prey to sustain themselves and feed their young (Nicoll et al. 2003, Senapathi et al. 2011). Exposure to heavy and prolonged rainfall could also be a direct cause of mortality through hypothermia, especially for chicks if nests are flooded (Senapathi et al. 2011). Future management of this species may need to incorporate strategies to mitigate the impacts of increasing rainfall.

References:

Fordham, D. A. and Brook, B. W. (2010) Why tropical island endemics are acutely susceptible to global change. Biodiversity and Conservation 19(2): 329‒342.

Jentsch, A. and Beierkuhnlein, C. (2008) Research frontiers in climate change: Effects of extreme meteorological events on ecosystems. Comptes Rendus Geoscience 340: 621‒628.

Nicoll, M. A. C., Jones, C. G. and Norris, K. (2003) Declining survival rates in a reintroduced population of the Mauritius kestrel: evidence for non-linear density dependence and environmental stochasticity. Journal of Animal Ecology 72: 917‒926.

Senapathi, D., Nicoll, M. A. C., Teplitsky, C., Jones, C. G. and Norris, K. (2011) Climate change and the risks associated with delayed breeding in a tropical wild bird population. Proceedings of the Royal Society B 278: 3184‒3190.

Inspirational Female Scientists #women1918

100 years ago today the UK parliament reformed the electoral system in Great Britain by permitting women over the age of 30 to vote. Unfortunately, there were terms to the act that meant women either had to be a member or married to a member of the Local Government Register, a property owner, or a graduate voting in a University constituency. However, crucial and progressive steps had been taken for women’s rights, and it is the same for today as it was 100 years ago, that more is needed to be done to ensure global gender equality.

At Social Metwork HQ, we have taken our time to reflect and be encouraged by inspirational female scientists. Different students across the department have written short paragraphs on female scientists that have inspired them to where they are today. If you have any other suggestions for inspirational scientists, please feel free to leave us a comment.

Amelie Emmy Noether – Kaja Milczewska

emmy-noether-2A true revolutionary in the field of theoretical physics and abstract algebra, Amelie Emmy Noether was a German-born inspiration thanks to her perseverance and passion for research. Instead of teaching French and English to schoolgirls, Emmy pursued the study of mathematics at the University of Erlangen. She then taught under a man’s name and without pay because she was a women.  During her exploration of the mathematics behind Einstein’s general relativity alongside renowned scientists like Hilbert and Klein, she discovered the fundamentals of conserved quantities such as energy and momentum under symmetric invariance of their respective quantities: time and homogeneity of space. She built the bridge between conservation and symmetry in nature, and although Noether’s Theorem is fundamental to our understanding of nature’s conservation laws, Emmy has received undeservedly small recognition throughout the last century.

Claudine Hermann – Helene Bresson

Claudine-HermannClaudine Hermann is a French physicist and Emeritus Professor at the École Polytechnique in Paris. Her work, on physics of solids (mainly on photo-emission of polarized electrons and near-field optics), led to her becoming the first female professor at this prestigious school. Aside from her work in Physics, Claudine studied and wrote about female scientists’ situation in Europe and the influence of both parents’ works on their daughter’s professional choices. Claudine wishes to give girls “other examples than the unreachable Marie Curie”. She is the founder of the Women and Sciences association and represented it at the European Commission to promote gender equality in Science and to help women accessing scientific knowledge. Claudine is also the president of the European Platform of Women Scientists which represents hundreds of associations and more than 12,000 female scientists.

Katherine Johnson – Sally Woodhouse

26646856911_ca242812ee_o_1For most people being handpicked to be one of three students to integrate West Virginia’s graduate schools would probably be the most notable life achievements. However for Katherine Johnson’s this was just the start of a remarkable list of accomplishments. In 1952 Johnson joined the all-black West Area Computing section at NACA (to become NASA in 1958). Acting as a computer, Johnson analysed flight test data, provided maths for engineering lectures and worked on the trajectory for America’s first human space flight.

She became the first woman to receive an author credit on a Flight Research Division report in 1960 and went on to author or co-author 26 research reports. Johnson is perhaps best known (in part due to the excellent feel good film Hidden Figures) for her work on the flight trajectory for John Glenn’s 1962 orbital mission.

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She was required to check the calculations of NASA’s IBM computer and Glenn is reported to have asked for her to personally check the coordinates.

“GET THE GIRL TO CHECK THE NUMBERS… IF SHE SAYS THE NUMBERS ARE GOOD, I’M READY TO GO.”

Katherine was also involved in calculations for the Apollo missions trajectories, including Apollo 11. In 2015 she was presented with the Presidential Medal of Freedom by Barack Obama.

Marie Tharp – Caroline Dunning

World War II was an important period in terms of scientific advance. In addition, it enabled more women to be trained in professions such as geology, at a time when very few women were in earth sciences. One such woman was Marie Tharp. Following the advancement of sonar technology during WWII, in the early 1950s, ships travelled across the Atlantic Ocean recording ocean depth. maria-tharp-oceanWomen however were not allowed on such ships, thus Marie Tharp was stationed in the lab, checking and plotting the data. Her drawings showed the presence of the North Atlantic Ridge, with a deep V-shaped notch that ran the length of the mountain range, indicating the presence of a rift valley, where magma emerges to form new crust. At this time the theory of plate tectonics was seen as ridiculous. Her supervisor initially dismissed her results as ‘girl talk’ and forced her to redo them. The same results were found. Her work led to the acceptance of the theory of plate tectonics and continental drift.

Ada Lovelace – Dominic Jones

ada-lovelace-20825279-1-402Ada Lovelace was a 19th century Mathematician popularly referred to as the “first computer programmer”. She was the translator of “Sketch of the Analytical Engine, with Notes from the Translator”, (said “notes” tripling the length of the document and comprising its most striking insights) one of the documents critical to the development of modern computer programming. She was one of the few people to understand and even fewer who were able to develop for the machine. That she had such incredible insight into a machine which didn’t even exist yet, but which would go on to become so ubiquitous is amazing!

Drs. Jenni Evans, Sukyoung Lee, and Yvette Richardson – Michael Johnston

Leading Scientists at Penn State University, Drs. Jenni Evans, Sukyoung Lee, and Yvette Richardson serve as role models for students in STEM subjects. The three professors are active in linking their research interests to not only education but also science communication, and government policy. Between them, they highlight some of the many avenues a career in STEM can lead to. Whether its authoring a widely used textbook, leading advisory panels, or challenging students throughout their time in higher education – these leaders never cease to be an inspiration.

 

Climate model systematic biases in the Maritime Continent

Email: y.y.toh@pgr.reading.ac.uk

The Maritime Continent commonly refers to the groups of islands of Indonesia, Borneo, New Guinea and the surrounding seas in the literature. My study area covers the Maritime Continent domain from 20°S to 20°N and 80°E to 160°E as shown in Figure 1. This includes Indonesia, Malaysia, Brunei, Singapore, Philippines, Papua New Guinea, Solomon islands, northern Australia and parts of mainland Southeast Asia including Thailand, Laos, Cambodia, Vietnam and Myanmar.

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Figure 1: JJA precipitation (mm/day) and 850 hPa wind (m s−1) for (a) GPCP and ERA-interim, (b) MMM biases and (c)–(j) AMIP biases for 1979–2008 over the Maritime Continent region (20°S–20ºN, 80°E–160ºE). Third panel shows the Maritime Continent domain and land-sea mask

The ability of climate model to simulate the mean climate and climate variability over the Maritime Continent remains a modelling challenge (Jourdain et al. 2013). Our study examines the fidelity of Coupled Model Intercomparison Project phase 5 (CMIP5) models at simulating mean climate over the Maritime Continent. We find that there is a considerable spread in the performance of the Atmospheric Model Intercomparison Project (AMIP) models in reproducing the seasonal mean climate and annual cycle over the Maritime Continent region. The multi-model mean (MMM) (Figure 1b) JJA precipitation and 850hPa wind biases with respect to observations (Figure 1a) are small compared to individual model biases (Figure 1c-j) over the Maritime Continent. Figure 1 shows only a subset of Fig. 2 from Toh et al. (2017), for the full figure and paper please click here.

We also investigate the model characteristics that may be potential sources of bias. We find that AMIP model performance is largely unrelated to model horizontal resolution. Instead, a model’s local Maritime Continent biases are somewhat related to its biases in the local Hadley circulation and global monsoon.

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Figure 2: Latitude-time plot of precipitation zonally averaged between 80°E and 160°E for (a) GPCP, (b) Cluster I and (c) Cluster II. White dashed line shows the position of the maximum precipitation each month. Precipitation biases with respect to GPCP for (d) Cluster I and (e) Cluster II.

To characterize model systematic biases in the AMIP runs and determine if these biases are related to common factors elsewhere in the tropics, we performed cluster analysis on Maritime Continent annual cycle precipitation. Our analysis resulted in two distinct clusters. Cluster I (Figure 2b,d) is able to reproduce the observed seasonal migration of Maritime Continent precipitation, but it overestimates the precipitation, especially during the JJA and SON seasons. Cluster II (Figure 2c,e) simulate weaker seasonal migration of Intertropical Convergence Zone (ITCZ) than observed, and the maximum rainfall position stays closer to the equator throughout the year. Tropics-wide properties of clusters also demonstrate a connection between errors at regional scale of the Maritime Continent and errors at large scale circulation and global monsoon.

On the other hand, comparison with coupled models showed that air-sea coupling yielded complex impacts on Maritime Continent precipitation biases. One of the outstanding problems in the coupled CMIP5 models is the sea surface temperature (SST) biases in tropical ocean basins. Our study highlighted central Pacific and western Indian Oceans as the key regions which exhibit the most surface temperature correlation with Maritime Continent mean state precipitation in the coupled CMIP5 models. Future work will investigate the impact of SST perturbations in these two regions on Maritime Continent precipitation using Atmospheric General Circulation Model (AGCM) sensitivity experiments.

 

 

References:

Jourdain N.C., Gupta A.S., Taschetto A.S., Ummenhofer C.C., Moise A.F., Ashok K. (2013) The Indo-Australian monsoon and its relationship to ENSO and IOD in reanalysis data and the CMIP3/CMIP5 simulations. Climate Dynamics. 41(11–12):3073–3102

Toh, Y.Y., Turner, A.G., Johnson, S.J., & Holloway, C.E. (2017). Maritime Continent seasonal climate biases in AMIP experiments of the CMIP5 multimodel ensemble. Climate Dynamics. doi: 10.1007/s00382-017-3641-x

Why become a Royal Meteorological Society Student member?

This week the Royal Meteorological Society (RMetS) published their strategic plan for the period of 2018 to 2020, and here at Social Metwork HQ we thought it would be a splendid idea to reflect on the benefits of being a student member of the Royal Meteorological Society.

An important benefit in my opinion is that when becoming a member of RMetS you join a well-established community who hold enthusiasm about the weather and climate at its core. Members come from all corners of the world and at different stages of their career spanning the entire range: from the amateur weather enthusiasts to professionals.  nicole-kuhn-450747As a student, being an RMetS member can lead to conversations that could develop your career and bring unexpected opportunities. This has been greatly enhanced with the RMetS mentoring scheme.

RMetS host many different types of meetings, including annual conferences, meetings hosted by regional centres, and national meetings. Additional gatherings are held by special interest groups, ranging from Weather Arts & Music to Dynamical Problems. Meetings on a regional and national scale provide a platform for discussion and learning amongst those in the field. DEhXj9AXkAARyMM.jpg largeFor a student, the highlight in the RMetS calendar is the annual student conference. Every year, sixty to eighty students come together to present their work and develop professional relationships that continue for years to come. This year’s conference is hosted at the University of York on the 5th and 6th July 2018 (more information). After two student conferences under my belt (see previous blog post), I would highly recommend any early career research scientist attending this event. It serves as a platform to share their own work in a friendly atmosphere and be inspired by the wider student community.

nasa-63030Other benefits to becoming an RMetS student member include eligibility to the Legacies Fund, grants and fellowships, and receiving a monthly copy of Weather magazine. Most importantly though, through becoming a RMetS member you support a professional society who are committed to increasing awareness of the importance of weather and climate in policy and decision-making. Alongside this week’s publication of RMetS’ strategic plan, both the Met Office and NASA have published press releases stating that 2017 was the warmest year on record without El Niño. The atmosphere and oceans of our planet are changing at unprecedented rates: rising sea levels, reductions in Arctic sea-ice, and an increased frequency of extreme weather events to name but a few climate change impacts. Becoming an RMetS student member does not only benefit your career and knowledge, but also supports a society that is committed to promoting and raising awareness of weather and climate science.

VMSG and COMET 2018 (or a Tale of Two Conferences)

The Volcanic and Magmatic Studies Group (VMSG) held a conference from the 3-6th of January in Leeds. The Centre for Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET) held a student conference from 8-9th January in Cambridge. It was a conference double-whammy about all things volcanic – heaven!

VMSG is a joint special interest group of the Mineralogical Society of Great Britain and Ireland and the Geological Society of London. The VMSG conference is a fairly small affair, with about 200 in attendance, and it brings together research in geochemistry, seismology, volcanology and related fields. Because of its size, it’s a nice informal space where there is a focus on students presenting their work to the VMSG community, but anyone is free to present their research.

Talks ranged from how tiny fossils, called diatoms, became trapped in a pyroclastic density current, to modelling of lava domes, to how local people interact with the volcano they live on at Masaya, to every aspect of volcanology you can think of. The final talk was definitely a highlight – with everyone in 3D glasses to look at volcanic plumes across Russia, it really brought the satellite images to life (and we got to keep the glasses).

90 posters on a variety of topics were presented, the majority of which were by students (I was one of them). There was of course an obligatory dinner and disco to round off the second day of talks, and a great chance to network with other people from VMSG.

For the best poster title of the conference, you need look no further than this gem.

The conference also provides workshops on different aspects of research, with sessions on writing papers, diffusion modelling and InSAR to name a few. These were hosted on the 6th at the University of Leeds Environment and Earth Sciences Department, and comprised a full day of talks and labs so you could get to grips with the techniques you were being shown. I attended the InSAR workshop, which gave a good introduction to the topic of comparing two satellite images and seeing where the ground had moved. There was also a session on deformation modelling in the afternoon and playing with bits of code.

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An afternoon of modelling InSAR deformations and code – hill-arity ensued.

Then it was onto the second leg of the conferences, which took the action to Cambridge, where students that are part of COMET met up to discuss work and attend talks from 8-9th January.

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Gneiss weather in Cambridge!

COMET is a National Environment Research Council Centre of Excellence, it comprises a group of researchers that uses remote and ground sensed data and models to study earthquakes and volcanoes. They also work with the British Geological Survey and the European Space Agency, and fund PhD projects in related fields.

The meet-up of students comprised two days of talks from students, with some keynote speakers who had been past members of COMET that had gone on to careers outside of academia. The talks from second and third years included: remote sensing and InSAR being used to examine tectonic strain in the East African Rift Valley and slip (movement) rates along faults in Tibet, modelling how gas bubbles in magma change the more crystals you add to the magma, and using cosmogenic isotopes to work out slip rates on a fault in Italy.

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The Department had cabinets and cabinets of samples that rocked.

First years are also given the chance to give a talk lasting 5 minutes, so I filled people in on what I’d been up to in the past four months – lots of data collection! My project will be using satellite data to look at the varied eruption behaviour of Bagana volcano in Papua New Guinea, with a view to modelling this behaviour to better understand what causes it. Bagana has a tendency to send out thick lava flows in long pulses and let out lots of gas, and occasionally then violently erupt and let out lots of ash and hot pyroclastic density currents. But it is very understudied, as it is so remote – so there’s lots still to be learnt about it!

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Me with my poster (I’ve run out of geology puns).

The meet-up also included a fancy meal in Pembroke College’s Old Library, with candles and it felt a bit like being at Hogwarts! Then it was back to Reading, thoroughly worn out, but with lots of ideas and many useful contacts – VMSG2019 is in St. Andrews and I can’t wait.

Deficiencies in climate model simulations of the seasonal rains in Africa

Email: c.m.dunning@pgr.reading.ac.uk

‘When is the wet season in Britain?’ a new student from Botswana asked me once. ‘Errrr, January-December?’ I replied flippantly. But in Botswana, and across much of Africa they experience one or two well-defined wet seasons per year, when the majority of the annual rainfall occurs. The timing and length of this wet season(s) is of significant societal importance; it replenishes water supplies used for drinking and other domestic purposes, affects the agricultural growing seasons and impacts the lifecycle of a number of vectors associated with the transmission of diseases such as malaria and dengue fever. Delays in the onset, or even failure of the wet season, can lead to reduced yields and potential food insecurity.

Future changes in climate will not be felt solely through changes in mean climate; projected shifts in atmospheric circulation patterns will also alter seasonality. Africa is acutely vulnerable to the effects of climate change so understanding future changes in the seasonal cycle of African precipitation is of utmost importance in establishing appropriate adaptation strategies. In order to produce reliable projections of seasonality, we require models to contain an accurate representation of current seasonality.

In our recent study we use a novel method to diagnose progression of the rainy seasons across continental Africa and identify important deficiencies in the climate simulations (a previous blog post and paper describes this method).

Firstly, when we use the method of Dunning et al. (2016) to identify the wet seasons in satellite-based precipitation estimates, atmosphere-only and coupled climate model simulations we find that the rainy seasons are differentiated more clearly from the dry seasons (shown by larger differences in the average rainfall per rainy day; Figure 1) than when fixed meteorological seasons (OND, MAM etc) are used, as this method accounts for interannual variability in seasonal timing and model timing biases.

figure_1anew

Figure 1. Average rainfall rate (mm day−1) during the wet/dry seasons over the Horn of Africa (a) and the Sahel (b) when defined using meteorological seasons (dashed bars) and dynamically varying seasons (Dunning et al. 2016, solid). See Figure 2 for a map of the regions.

Overall, climate model simulations capture the gross seasonal cycle of African precipitation on a continental scale, and seasonal timing exhibits good agreement with observations, however deficiencies manifest over key regions (Figure 2). The Horn of Africa (Somalia, southern Ethiopia, Kenya) experiences two wet seasons per year; the ‘long rains’ during March-May and the ‘short rains’ during October-November.  Whilst the simulations capture two wet seasons per year, they exhibit significant timing biases, with the long rains around 3 weeks late and the short rains nearly 4 weeks too long on average (Figure 2). Accounting for these biases may be crucial in interpreting the contrasting trend of observed declining rainfall during the ‘long rains’ in recent years and model projections of increasing ‘long rains’ rainfall in the future.

figure_4_regions_withbars_newlegend

Figure 2: Multi-model mean onset (open circles) and cessation (filled squares) for observations, atmosphere-only (AMIP) and coupled (CMIP) over selected regions (b). Shaded bars indicate the period of the wet season. For SWAC the mean annual regime onset/cessation in coupled simulations is plotted, along with mean onset/cessation for MIROC4h and BCC-CSM1-1-M (coupled simulations).

The most notable bias affects the southern coastline of West Africa, a region of complex meteorology with growing population and declining air quality. This region experiences the first wet season from April-June and the second wet season from mid-September-October, separated by the ‘Little Dry Season’ (LDS) in July-August. The LDS can be useful for weeding and spraying crops with pesticides between the two wet seasons, but can adversely affect crop yields if it is too long or pronounced. We find that simulations produce an unrealistic single summer wet season, with no mid-summer break in the rains and this is linked with biases in ocean temperature patterns. Given that climate simulations cannot capture the current seasonality, future projections for this region should be treated with caution.

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Figure 3: a) Location of the region that experiences the Little Dry Season (LDS; blue dots) and the SST region of interest (pink box). b) Mean annual cycle of rainfall in observations, atmosphere-only and coupled simulations over LDS region.

This work highlights important deficiencies in the representation of the seasonal cycle of rainfall by climate simulations with implications for the reliability of future climate projections and associated impact assessments, including water availability for hydropower generation, the length of the malaria transmission season and future crop yields.

The full paper can be found here:

Dunning, C.M., Allan, R.P. and Black, E. (2017) Identification of deficiencies in seasonal rainfall simulated by CMIP5 climate models, Environmental Research Letters, 12(11), 114001, doi:10.1088/1748-9326/aa869e