Global Environmental Change class content week 7- 9 (Unit 3)

NASA’s global temperature analysis is drawn from data collected by

weather stations and Antarctic research stations, as well as instruments mounted on ships and ocean buoys

NASA scientists analyze these measurements to account for

uncertainties in the data and to maintain consistent methods for calculating global average surface temperature differences for every year.

NASA uses the period from 1951-1980 as a

baseline to understand how global temperatures change over time. That baseline includes climate patterns such as La Niña and El Niño, as well as unusually hot or cold years due to other factors, ensuring it encompasses natural variations in Earth's temperature

NASA explains work on global mean temperature by another agency called the

US National Oceanic and Atmospheric Administration (NOAA).

In contrast to NASA’s conclusion that 2022 was the fifth hottest year on record, NOAA found 2022 to be the

sixth hottest

A separate, independent analysis by the National Oceanic and Atmospheric Administration (NOAA) concluded that the global surface temperature for 2022 was the

sixth highest since 1880.

NASA acknowledges that NOAA landed at a different conclusion, but in the big picture, temperature trend

lines are very similar.

The different conclusions between NASA and NOAA are in large part

attributable to the use of different baseline periods.

Global surface temperatures are a broadly used indicator of climate change and defined as an

essential climate variable (ECV) by the Global Climate Observing System

ECV’s are

Essential Climate Variables

The ECV concept has been globally adopted as the guiding basis for observing climate because it helps

researchers around the world to coordinate what data to collect, how to put it together into temporal datasets, and how to analyze those datasets to make estimates and projections about temperature

The first estimate of a globally averaged surface temperature was produced approximately

80 years ago

Today, typical global estimates are derived from combining

land surface air temperature (LSAT) captured at fixed meteorological sites with sea surface temperature (SST) estimates recorded on/by ships and buoys

Global Surface Projections generated through models use air surface temperature, which is

equivalent to LSAT and marine air temperature (MAT).

One challenge is that LSAT datasets gathered in place over long periods of time may contain

‘artifacts’ that arise from various factors, including station moves, instrument changes, observer changes, automation, time of observation biases, microclimate exposure changes, and urbanization

Earth observation satellites are increasingly used to gather

data from which global temperature estimates can be derived and that can feed into models that make projections about global temperature changes in the future

Satellite-gathered data is often used in combination with

data gathered from specific sites (i.e., ‘in situ’).

Both Satellite and specific sites can be used to

compare against each other, improving estimates overall.

Thorne 2021 states that “It is unequivocal that the global surface temperatures have warmed since the instigation of instrumental records. This change has not been

linear and has varied substantially geographically. Important uncertainties and challenges remain to be addressed regarding, for example, data availability, measurement understanding, and providing high temporal resolution data suitable for many applications.

What is the first key computer-based model developed and used by climate and other environmental change scientists

To derive indicator estimates

What is the second key computer-based model developed and used by climate and other environmental change scientists

To make projections about changes in the future

What is the third key computer-based model developed and used by climate and other environmental change scientists

To build understanding of how different variables relate to one another within global systems over various periods of time and at different spatial scales

Less than a century ago, computers, as we know them, did not exist and scientists who were trying to understand atmospheric and other biophysical phenomenon

sketched out basic numerical equations by hand onto paper.

An early book called Weather Prediction by Numerical Process was published in 1922 by English mathematician and meteorologist Lewis Fry Richardson. He proposed a new idea, which was to

use sets of mathematical equations called ‘differential equations’ to represent and describe the atmosphere as a grid network of interrelated cells.

A lot has changed since the time of Lewis Fry Richardson and his book in 1922. Today we have computer-based mathematical models based on scientific laws that describe

physical, chemical, and biological mechanisms known to underlie climate at different scales.

According to Carbon Brief, a typical global climate model contains enough computer code to fill

18,000 pages of printed text and takes hundreds of scientists many years to build and refine

The code within the computer systems

contains equations that represent physical, chemical, and biological mechanisms and provides instructions for how they relate together with respect to climate.

The largest global models often run on one or more

supercomputers, some of which can be the size of a tennis court!

The earliest category of climate model, Energy Balance Models (EBMs), considers

energy entering the Earth’s atmosphere from the sun and the heat released back out to space

the only variable (Energy Balance Model) EBMs calculate is

surface temperature

EBMs were important to the early history of climate modelling and to building consensus that greenhouse gas emissions drive global warming (as we discussed in Unit 01). However,

climate science continues to evolve, and there are demands from the public, decision-makers, and others for more types of information about a wider range of variables that can be used as indicators within efforts to mitigate and adapt to global environmental change.

What are GCM’s

General Circulation Models, also sometimes called Global Climate Models

GCM’s were an important development in climate science. GCMs are more

complex than EBMs in that they capture flows of air, water in the atmosphere, oceans, and the transfer of heat

It is possible to link or couple GCMs together to simulate

exchanges and other interactions between different processes and biophysical systems

One thing that the Global-scale Coupled Climate Models infographic above shows is that ocean water and processes were brought into GCMs starting in around the mid-1960s, and sea ice starting in the late

1970’s

Satellites and remote sensing have been used to assess global rates of sea level change since at least the early

1990’s

In many places, sea level has indeed risen during this period. Gehrels and Garrett (2021) state:

“direction of sea level-changes, positive or negative, depends on the time scale of observations and the spatial scale under consideration” […] “Linear trends over the period 1993-present show that global sea level is rising on average at a rate of about

3.4 mm/a. However, regional variability is significant. Some parts of the world’s oceans have experienced rates of sea level rise that far exceed the global average (>10 mm/a in places), while in others, sea level has fallen” (p. 205-206).

However, overall, there is international consensus that:

“the main contributors to sea level rise since 1993 have been

thermal expansion of the oceans (1.4 mm/a) and melting ice from small glaciers and ice caps (0.6 mm/a), with smaller amounts from the Greenland Ice Sheet and peripheral glaciers (0.5 mm/a) and the Antarctic Ice Sheet (0.3 mm/a).

Human activity is required to explain the observed thermal expansion, glacier ice loss, and changes in terrestrial water storage. Volcanic eruptions have reduced the rate of mean sea level rise, and some of the 20th-century rise in sea level was delayed by the eruptions of Krakatoa in 1886 and Pinatubo in 1991, temporarily masking the impact of anthropogenic effects on sea level rise. Nevertheless,

on both regional and global scales, sea level rise is now beyond the limits of natural internal variability. At least 1 mm/a of global sea level rise during the 20th century can be attributed to anthropogenic forcing (Human Activity)

Model experiments show that 20th-century sea level rise cannot be explained by natural processes alone. Anthropogenic forcing by greenhouse gasses has become a

dominant cause of sea level rise, generating thermal expansion of ocean waters and melting of land-based ice. Modern rates of sea level rise started about 100 years ago, and it is virtually certain that the 20th century rise is faster than rates over the preceding three millennia

temperature is one of many climate

Variables

Weather is the state of

the air, temperature, and atmosphere in a given place at a specific moment in time

Climate is a

statistical description of mean and variability in surface variables, like temperature and wind, over a period of time

Statistically speaking, extremes are

rare events happening in the tail of the distribution of a climate variable [temperature is one example of a climate variable].

A distinction between extreme weather and extreme climate events can be made, for instance, on the basis of their

temporal and spatial occurrence.

The timescale of extreme weather events typically ranges from minutes to days, such as a storm or a heavy precipitation event, while an extreme climate event typically has a timescale of

months or years, such as a prolonged heatwave or drought

Weather and climate operate at different

spatial and temporal scales

Specific events are identified as extreme when

they sit at the tail end of the distribution of one or more climate variables

Surface temperature is one, but certainly not the only

climate variable

Attributing extreme heat events to climate change requires a special modeling setup. For this purpose, climate model simulations with greenhouse gas concentrations at today's levels are compared with simulations with greenhouse gas concentrations fixed at

preindustrial levels.

for looking at temperatures with special modeling, a world with climate change is compared with a hypothetical world where climate change did not happen. Results from such studies consistently reveal a clear

human influence on the historical evolution of extreme temperatures. For example, more than 75% of moderate and hot extremes under current climate conditions can be attributed to climate change

Attributing trends in extreme precipitation, floods, and droughts to human influence is difficult due to the

low signal-to-noise ratio and the mentioned limitations in observations.

similar as for temperature extremes, climate scientists are trying to quantify the change in occurrence probability of extreme precipitation events given the human influence on the climate system. This relatively new field is called

probabilistic event attribution

Temperature extremes are comparably well covered in observations, and significant increases in hot extremes were identified in many parts of the world, which can, to a large extent, be attributed to

human-made climate change.

Trends in precipitation show higher spatial and temporal variability. Yet, the fraction of observation stations showing statistically significant increases in

extreme precipitation is much larger than the fraction exhibiting decreases

For tropical cyclones, no clear trends have been observed in terms of associated rainfall globally. However, for some individual tropical cyclones, part of their extreme rainfall could be attributed to

Climate Change

An action or actions taken with the intention of reducing harm, damage, and vulnerability to present and near-future global environmental change

This is talking about adaption

Examples of adaption include

tending to mangroves in tropical coastal areas that prevent erosion and protect communities from future flooding caused by sea level rise; planting diverse seed species so that agricultural crops can tolerate a wider range of environmental conditions

Adaptation needs to consider future

conditions, including extremes.

The three concepts from Week 4 are:

1: Common But Differentiated Responsibility,

2: Double Exposure

3: Climate Justice

Climate vulnerability assessment is an advanced field of study and area of real-world practice; the framework

immediately above is often the basis upon which evidence-based assessments are designed and undertaken.

In Climate vulnerability, both

Quantitative and qualitative information pertinent to a place and/or different groups of people are gathered and analyzed in ways that result in measures and detailed descriptions of exposure, sensitivity, and adaptive capacity.

Regarding Climate vulnerability, exposure is the

Nature and degree to which people and/or place are exposed to significant climate variations.

Regarding Climate vulnerability, Sensitivity is the

The degree to which people and/or place are affected, either adversely or beneficially, by climate-related stimuli.

Regarding Climate vulnerability, Adaptive Capacity is the

The capacity of human socio-economic systems and institutions to build/plan infrastructure, adjust to potential damage, or to mediate/respond to consequences in place.