In-situ Measurements of Land and Atmosphere

Read...

In-situ measurements of the land and atmosphere

In-situ measurements require that the instrumentation be located directly at the point of interest and in contact with the subject of interest. For those who took Latin in high school, you may remember that “in situ” means “in position.” Going back to our vital signs analogy from before, this would be the equivalent of a thermometer that was placed under your tongue. Measuring the air temperature with a thermometer is the easy climate analog – we are physically measuring the temperature at a specific location, but having the air make direct contact with the thermometer gives us our reading. The same thing holds for taking wind measurements (wind striking an anemometer or wind vane) or measuring precipitation (rainfall falling into a rain gauge).

A great deal of our in-situ measurement toolbox centers on the land surface, where humans live. As implied before, one of the most important ECVs for studying climate is near-surface temperature. This is the temperature outside that you and I experience at any given time, and is the temperature we are all familiar with being reported by our local weather forecasters. It is inexpensive to measure, many of you may already do this, and is almost always reported from a surface weather station, whether those be at airports or in backyards.

Thermometer records from weather stations, islands, and ships provide us with more than a century of reasonably good global estimates of surface temperature change. Measurements were historically made using mercury or alcohol thermometers, which were read manually and recorded by hand at either specified intervals or just when convenient. Over the past few decades, these observations are increasingly made using electronic sensors that transmit data without the need for human intervention. Heck, even things like your car and smartphone likely have the capability to measure temperature automatically! Some regions, like the Arctic and Antarctic, and large parts of South America, Africa, and Eurasia, have not been as well sampled over the past century or so, but records in these regions become more available as we moved into the mid and late 20th century.

These data can be reported as a time series as we discussed in the previous lesson but given that we are interested in the surface temperature and how it has evolved over the last ~200 years, we typically take these temperatures, scattered at various points and times, and merge them into a single organized dataset that can be visualized as a map. A key benefit to this approach is it reduces the potential impacts of outliers and bad data while giving us a “global” view of the planet. The figure below shows the result of this as derived by the Berkely Earth project. The scientists working on the dataset have merged all in-situ surface temperature observations from 2022 and then compared that result to the 1951-1980 global average.

Text description of the Surface Temperature Anomaly Map.

A color-coded map of the globe, visually representing the temperature anomalies for the year 2022. It features a gradient ranging from blue to red, where blue areas indicate lower temperatures and red areas signify higher temperatures when compared to the average temperatures recorded from 1951 to 1980. The map is set against a light gray background, enhancing the visibility of the color gradients. Prominent landmasses, including North America, South America, Europe, Africa, Asia, and Australia, can be discerned, with varying intensities of colors representing the temperature deviations across different regions. The upper right corner displays the year "2022" in bold, black text, while the bottom of the image includes a horizontal scale legend indicating temperature anomalies in degrees Celsius, ranging from a minimum of -6°C (dark blue) to a maximum of +6°C (dark red).

Credit: Global Temperature Report for 2022, Berkeley Earth is licensed under CC BY-NC 4.0 International

Moving one step further, all of these data points and different locations and times can be merged together to form a single global mean. This is the value that is frequently seen in the media or other outlets when discussing climate change over the past hundred years. Note that there is not one specific way to calculate a single global mean – see the graph below, which shows six different time-series of the global mean temperature anomaly! It’s important to note, however, that while the lines differ slightly even though they are generally using the same observational record, the overall behavior and trends of the curves are very similar, no matter which strategy is employed.

Text description of the Global mean temperature image.

A line graph depicting the global mean temperature anomaly compared to the average from 1850 to 1900. The graph has a white background with a grid overlay for easier reading. The x-axis represents the years, ranging from approximately 1850 to 2022, and is labeled accordingly. The y-axis indicates temperature anomalies in degrees Celsius, with values spanning from -0.4°C to 1.4°C.

There are multiple lines on the graph, each representing different datasets or methodologies for calculating the global mean temperature. Each line is represented in a unique color:

• HadCRUT5 (black)
• NOAA GlobalTemp (orange)
• GISTEMP (yellow)
• Berkeley Earth (blue)
• JRA-55 (green)
• ERA5 (light blue)
  The lines show varying trends over time but generally indicate a rise in temperature anomalies, particularly noticeable after the mid-20th century. A bold title at the top reads “Global mean temperature Compared to 1850-1900 average.”

Credit: lobal Mean Temperature Compared to 1850-1900 Average, World Meteorological Organization, CC BY-NC-ND 4.0 DEED