Posts filed under Environment (58)

We’re seeing a lot of international news stories about cold weather in the US, and here in NZ we’re also seeing a lot of stories about hot weather locally and in Australia. You might think from the news coverage that the northern hemisphere is currently colder than usual and the southern hemisphere is currently warmer than usual.

This map (from) shows ‘temperature anomaly’, that is, the difference between the temperature today and the 1979-2000 average for the time of year.

There are some cold spots on the map: the north-east of North America and parts of northern Russia are much colder than usual. There are also hot spots, in Alaska and in the Arctic Sea.   And as the summaries under the map show, the northern hemisphere is more unusually hot (on average) than the southern hemisphere.

Weather is what matters to us day to day: especially the weather around us and the weather in places with English-speaking television stations.  That can give a very misleading view of the state and trend of global climate.

From the MetService rain radar

If the band of rain were moving north-east, small uncertainties in its motion and orientation would mean that you’d know there would be half an hour of rain in Auckland, but not exactly when.

If it were moving south-east (as it is), small uncertainties in the motion and orientation mean that you know it will rain for a long time somewhere, but not exactly where.

One way to communicate the difference between these two predictions would be to show a set of possible realisations of rainfall.  For NW movement, you’d get a set of curves each with a single hump but at different times. For SW movement you’d get a much wider range of curves, where some showed no rain and others showed half a day or all day. I don’t know enough about ensemble forecasting to be sure, but I think this would be feasible

In principle, the common ‘patchy torrential downpours’ Spring rain pattern would show as rain curves each with different short periods of rain. I don’t think the technology is up to that using genuine predictions, but it might be possible to predict that we’re going to get that sort of weather and simulate the ensemble curves.

Current forecast summaries are mostly (except for hurricane paths) about averages: the probability of rain,  the expected amount, the worst-case amount. As technology progresses we will increasingly be able to do better than averages.

It’s time again for the only bogus poll that StatsChat endorses: the New Zealand Bird of the Year.

Why is Bird of the Year ok?

• No-one pretends the result means anything real about popularity
• The point of the poll is just publicity for the issue of bird conservation
• Even so, it’s more work to cheat than for most bogus polls

Why takahē?

• Endangered
• Beautiful (if dumb)
• Very endangered
• Unusual even by NZ bird standards: most of their relatives (the rail family) are shy little waterbirds.

(A sora, a more-typical takahē relative, by/with ecologist Auriel ‘@RallidaeRule’ Fournier)

Auckland Transport released new patronage data, and FigureNZ tidied it up to make it easily computer-readable, so I thought I’d look at some of it.  What I’m going to show is a decomposition of the data into overall trends, seasonal variation, and random stuff just happening. As usual, click to embiggen the pictures.

First, the trends: rides are up.

It’s hard to see the trend in ferry use, so here’s a version on a log scale — meaning that the same proportional trend would look the same for all three modes of transport

Train use is increasing (relatively) faster than bus or ferry use.  There’s also an interesting bump in the middle that we’ll get back to.

Now, the seasonal patterns. Again, these are on a logarithmic scale, so they show relative variation

The clearest signal is that ferry use peaks in summer, when the other modes are at their minimum. Also, the Christmas minimum is a bit lower for trains: to see this, we can combine the two graphs:

It’s not surprising that train use falls by more: they turn the trains off for a lot of the holiday period.

Finally, what’s left when you subtract the seasonal and trend components:

The highest extra variation in both train and ferry rides was in September and October 2011: the Rugby World Cup.

Another nice Herald interactive, this time of housing affordability.

Affordability comes in two parts: down payment and monthly mortgage costs. The affordability index from Massey University looks at monthly payments; this one looks at the 20% down payment.

The difference between Auckland and the rest of the country is pretty dramatic, but there are other things to see. Above, the centre of Auckland is much less expensive than the rest of the city: 75% of properties are valued at under $500,000 by CoreLogic.  That’s the apartments, but they mostly aren’t the sort of apartments people are planning to stay in long-term.

Another interesting feature for Auckland is that the neighbourhoods really are ordered in price — you don’t see the spatial trends changing as you move the slider, so there aren’t areas where the low-end houses are especially cheap and the high-end houses especially expensive.

You can also see the difficulty of relating valuations to prices. In Point Chev, the valuations say 70% of homes are valued at over $1 million. On the other hand, the median sale price is $990,00, so less than half the homes that changed hands went for over a million.

Both those numbers are correct. Well, ok,  I assume they are both correct; they are both what they are supposed to be.  It’s just that home sales aren’t a random sample of all homes.  But if the median sale price is $990k and the median valuation for all homes is $1.2m, you can see that interpreting these numbers is harder than it looks.

Every summer, the Department of Statistics offers scholarships to a number of students so they can work with staff on real-world projects. Oliver, right, is working on visualising conservation data with Associate Professor Rachel Fewster. Oliver explains:

“This summer project is called Maps, graphs, and data analysis for community conservation projects, and builds on my Honours project from the past year. It involves developing interactive applications that automate the display of catch data from various conservation projects around New Zealand.

“The aim of this project is to allow volunteers to engage with their data in more depth than ever before. After a day in the field, a conservation volunteer is able to go online and use these applications to produce maps or graphics to view their day’s work. The graphics illustrate exactly how a volunteer’s work is impacting their local environment and will ideally keep them motivated to continue with what they are doing.

“I graduated from the University of Otago in 2014 with a Bachelor of Science majoring in Statistics and minoring in Psychology, before completing an Honours degree in Statistics at the University of Auckland in 2015. In 2016, I plan on pursuing a Master of Science in statistics, completing this degree as a research masters.

“I enjoy statistics due to its numerous applications. Nowadays, data exists in almost every facet of life, and wherever there is data, we can use statistics to try and gain a deeper understanding of what is really going on around us.

“In my spare time this summer, I will, hopefully, be able to watch the Black Caps as they continue with their summer of cricket.”

Every summer, the Department of Statistics offers scholarships to a number of students so they can work with staff on real-world projects. Hubert, right, is working on ways to graphically represent community conservation efforts with Associate Professor Rachel Fewster. Hubert explains:

“Conservation efforts are needed to protect the natural flora and fauna of our beautiful country. This exciting project involves preparing and analysing data collected from volunteers involved in conservation efforts against pests such as rats.

“The data is analysed and uploaded to a website called CatchIT, which is an interactive website that allows the bait and trap information to be presented in graphic form to volunteers, which provides feedback on their pest-control efforts. The data comes to life on the screen, and this engages current and future volunteers in tracking the success of their pest-control projects.

“I am in the final year of my Bachelor of Science majoring in Statistics and Biological Science, having previously finished a Bachelor of Pharmacy (Hons). Statistics has a wide applicability to a wide range of disciplines, and appeals to me because I am passionate about the simple process of getting the most from raw data. It is a very rewarding process knowing that you can make the data more appealing and important to the end user.

“This summer, besides doing this studentship, I’ll be enjoying the sunshine, and relaxing on the beach with family and friends.”

The northern hemisphere is warmer than usual this Christmas, as you may have heard. To be precise, it’s about 1 Fahrenheit degree above the 1979-2000 average after seasonal adjustment. (via)

Parts of the northern hemisphere are a lot warmer than that, including many parts that have a concentration of news media with a seasonal shortage of stuff to report. It’s hot in the eastern US, and this quite reasonably gets more reporting that it being cold in Siberia.

When the US northeast has unusually cold or snowy periods in winter, you see lots of people carefully explaining how this is weather or short-term variation and doesn’t tell you much about long-term climate patterns.

I’m one of those people, so this year I’m making the same point about warm weather.  The northern hemisphere as a whole is warm by about what the well-known trend suggests. The strong El Niño causing weird local weather in the eastern US could definitely be due in part to the global trend, but conclusions about regional variation are much less reliable than conclusions about this CO2 stuff being a bit of a worry.

Like the snow last year, the hot Christmas this year is consistent with climate change predictions but doesn’t add importantly to the evidence. It’s dramatic that Baltimore is as warm as Auckland this Christmas, but compared to the mass of accumulated evidence on the subject, a few days freak weather in a small part of the world just doesn’t mean much.

Australia’s climate is weird, even in the relatively habitable bits such as Melbourne, so it makes for interesting graphs. This is going to be another post about aspect ratios and alignment in graphs and how to use them for things other than lying with statistics. (more…)

First, from Mother Jones magazine, via Twitter

The impact of the carbon tax looks impressive, but this is a bar chart — it starts at zero and they’ve only shown the top fifth of it.

They do link to the data, the quarterly Greenhouse Gas Inventory update.  In that report, Figure 8 is

The dotted line is the same data as the bar chart, except that the dotted line has data for every quarter and the bar chart has data only for the July-September quarter each year. And  the line chart has a wider range on the vertical axis — it doesn’t go down to zero, but it isn’t a bar chart, so it doesn’t have to. The other point about the line chart is that there’s a solid line there as well. The solid line is adjusted for seasonal variation and weather. If you wanted to know about real changes in how Australians are using energy, that’s the line you’d use.

Second, a beautiful map of CO₂ emissions from fossil fuel combustion, from the Washington Post via Flowing Data

The ‘vertical’ scale here is a colour scale; what’s misleading is that it’s a logarithmic scale. The map makes it look as if a large fraction of CO₂ emission comes from transporting stuff through empty areas, but the pale beige indicates emissions thousands of times lower than in the urban/suburban areas. Red ink isn’t anywhere close to being proportional to CO₂.