Angus Ferraro

A tiny soapbox for a climate researcher.


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EUMETSAT Conference 2014: Final highlights

2014-09-27 11.27.13

Headquarters of the WMO, which we visited during the conference for a discussion on the socioeconomic benefits of meteorological satellites.

The EUMETSAT Meteorological Satellites Conference 2014 featured a lot of new science. Two particular points which stood out to me was the assimilation of new products into numerical weather forecasting systems, and the use of satellite data in improving our conceptual understanding of weather systems.

Until this conference I was not aware how new it was to incorporate soil moisture into numerical weather forecasting systems. Such forecasting systems spend a good deal of resources on assimilating observational data to initialise the forecast. This is very important because, as pioneering work by Ed Lorenz showed back in the 1960s, tiny differences in the initial state of an atmospheric model (and of course the real atmosphere) can lead to huge differences in the resulting forecast, even for relatively short-range forecasts.

Soil moisture is clearly a useful thing to know about in our forecasts. For weather forecasts it mainly plays a role in supplying water for weather systems. Wet surfaces supply water to the atmosphere, causing or intensifying rainfall.

A few years ago soil moisture satellite products were not considered mature enough to assimilate into weather forecast systems. This is partly because our measurements were quite uncertain (we couldn’t attach very accurate numbers to them), but also because our uncertainty was poorly characterised (we didn’t know how accurate our measurements were). In a sense, the latter is more important. Like much of science, the point is not always knowing things exactly, but accepting that it’s impossible to achieve perfect accuracy and to at least know exactly how certain we are about a measurement (Tamsin Edwards has a related blog post focusing on climate rather than weather).

After some experimental studies showed the potential for soil moisture data to improve weather forecasts, operational forecasting centres across the world began to adopt this extra data source – the ones I heard about at the conference were ECMWF and the UK Met Office, but there are probably others.

Now let’s move to something less mathematical, but equally as important and exciting. On Thursday I listened to two excellent presentations on the Conceptual Models for the Southern Hemisphere (CM4SH) project. The rationale behind CM4SH is that the vast majority of weather forecasting ‘wisdom’ is derived from Northern Hemisphere perspectives, through an accident of history. But understanding the weather of the Southern Hemisphere isn’t as simple as flipping everything upside down. Although the physics of the weather is clearly the same, the actual meteorological situation in Southern Hemisphere countries is different. For example, South Africa lies in the midlatitude belt like Europe does, but it sits rather closer towards the Equator, so the same weather system could have different effects. The configuration of Southern Hemisphere land masses is very different, and that leads to rather different weather behaviour.

CM4SH is a collaboration between the national meteorological services of South Africa, Argentina, Australia and Brazil. The work focused on building up a catalogue of typical meteorological situations in different regions of the Southern Hemisphere, analysing similarities and differences. The international CM4SH team used Google Drive to build a catalogue of these situations, their typical causes, behaviour and effects. Satellite imagery is obviously a major part of the catalogue, as it allows forecasters to track the flow of moisture, presence of clouds, direction and strength of winds. The resulting catalogue allows Southern Hemisphere forecasters to classify meteorological situations and quickly find out the typical effects of different systems. For example, if a forecaster sees a particular meteorological configuration, they can quickly check the catalogue for the effects of similar situations in the past, and see that they need to assess the risk of, say, flooding, in a vulnerable region.

I think projects like this reflect the power of the Internet to supercharge our science. Earlier this week I wrote about how the data from the new GPM mission were available and easily accessible within weeks. GPM is a huge international collaboration combining the resources of a whole constellation of satellites. CM4SH is a project which makes use of expertise from four national meteorological services to create an unprecedented collaborative resource for forecaster training and education, freely available. The CM4SH catalogue will grow over time and become more refined – the beauty of collaborative projects like this is that, as long as someone does a little pruning now and then, they can only ever become more useful.

EUMETSAT Post 1: Challenges and advances in satellite measurement

EUMETSAT Post 2: Socioeconomic benefits of meteorological satellites

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EUMETSAT Conference 2014: Challenges and advances in satellite measurement

Atmospheric measurement is an extraordinarily difficult problem. It’s a fluid capable of remarkable feats of contortion, and it contains a number of important constituents, including one – water – which flits easily between solid, liquid and gaseous forms. Satellite instruments offer a unique way to measure the state of the atmosphere, viewing broad swaths of the planet from space.

I’m at the EUMETSAT Meteorological Satellites Conference in Geneva, which is as good a place as any to understand what a remarkable achievement this is. These are my highlights from the first two days, and reflect my particular interests, so I have probably missed a host of other interesting scientific advances.

A major theme of the ‘climate’ session at the conference was the problem of generating long-term climate records from satellite data that is often very choppy. Satellites and their instruments can have very short lifetimes, usually just a few years, though some (like the rather venerable 17-year-old TRMM) buck the trend. Satellites can only carry so much fuel to keep them in orbit, and their instrumentation gradually degrades over time in the harsh environment of space. To maintain a long-term record, you would want to send up identical instruments into identical orbits – but in reality this is not possible. The instruments themselves are made with extraordinary levels of precision, but their complex and delicate nature means it’s not actually possible to make them identical. They will usually have slightly different sensitivies. The satellites carrying them will have different orbits, which means they might measure different parts of the Earth at different times.

Changes like this can cause major stability problems for satellite records. Each time a new instrument goes up on a new satellite the record tends to ‘jump’. Common reasons for this include slight differences in the sensor’s sensitivity, and sampling changes due to the different orbit. As an example, rainfall in the Tropics usually peaks in the afternoon. If you send up a new instrument which passes over the Equator in the morning, it will look like rainfall has abruptly decreased compared to one that passes in the afternoon, but all that’s happened is that you’re measuring it at a different time. These so-called ‘inhomogeneities’ need correction if we are to stand a chance of using these records for studies of climate (which is the statistics of the atmosphere and oceans over decades – many satellite lifetimes).

The ‘climate’ session at EUMETSAT highlighted many approaches to such problems. There was also discussion of the potential for improving the physical consistency between datasets, so common ‘budgets’ can be closed. However, the fact that our observations sometimes don’t ‘add up’ is an important piece of information. It means we’re getting something wrong – but exactly what is of course a rather difficult question.

On Tuesday afternoon a session on precipitation measurement included some very impressive results from the new Global Precipitation Measurement (GPM) mission. A number of technological advances, combined with a unique approach of using two reference satellites to calibrate the measurements from a ‘constellation’ of 11 others, now provide unprecedented detail on Earth’s rain and snowfall. High-frequency microwave measurements combined with radar allow us to look at the icy parts of clouds and to see areas where even very light rain is falling. This allows us to look at, for example, tropical storms in a whole new light – and most importantly, because it’s based on such a huge array of measurement platforms, we won’t miss a single one.

Another impressive aspect of the GPM mission is the speed with which things have moved. Since its launch in February 2014 GPM has been providing huge streams of data, which an international team has worked on to convert to precipitation measurements. Within a short time the data were available to the public. The data were available to the world’s major weather forecasting centres within 2 weeks, allowing them to get a much better picture of the current state of the atmosphere (this is important because small errors in the initial state of the atmosphere can lead to large errors in a weather forecast). In short, GPM looks like a thoroughly modern measurement misson: an international collaboration, operating openly and with detailed documentation, providing timely and freely-available data. Plus it produces some cool graphics (see below).

One of the first storms observed by the NASA/JAXA GPM Core Observatory on March 17, 2014, in the eastern United States revealed a full range of precipitation, from rain to snow. Image Credit: NASA/JAXA

The day closed with a visit to the headquarters of the World Meteorological Organisation for presentations and discussions on the socioeconomic value of satellite data – that’s covered in another post.

EUMETSAT Post 2: Socioeconomic benefits of meteorological satellites. 

EUMETSAT Post 3: Final highlights.