159 Morrill South, UMass
“I just want to congratulate Ambarish on a very nice thesis; I enjoyed reading it.”~ Dissertation Committee Member Dr. Henry Diaz
I enjoyed the extremely detailed presentation too, but I must confess that chills ran up and down my spine on a few occasions. Dr. Ambarish Karmalkar was careful not to be alarmist as he reported findings on experiments forecasting regional climate changes in Costa Rica and its neighbors. Dr. Karmalkar explains: “The frequency of temperatures in the future is something we have not experienced in the modern period.” In the case of Central America in general, and Costa Rica in particular, he was referring to a probable future increase in the average temperature of 3-4 degrees Celsius (roughly 5-7 degrees Fahrenheit) before the end of this century. If this does not seem like a big deal, compare it to the temperature fluctuation that accompanies El Nino – a mere one degree – and all the weather we (US Americans) blame on that. Then imagine that already species are becoming extinct in the subtropical rain forests. The suddenly extinct (since 1989) Golden Toad, for instance, was once abundant in the Monte Verde Cloud Forest of Costa Rica.
Climate Change Predictions for Central America:
A Regional Climate Model Study
by Ambarish Karmalkar
Specifically, Dr Karmalkar’s dissertation research involved testing the reliability of the general circulation model that is used for regional climate modeling: PRECIS. He chose the region of Central America for a few specific reasons:
- more studies on biodiversity and climate change have been done in Costa Rica than anywhere else (so he has lots of material to compare and contrast in terms of results already collected)
- there is severe impact from changes in precipitation in the Yucatan (the ‘top’ or northern edge of Central America, dividing it from North America)
- Costa Rica meets the criteria for being a biodiversity hotspot: meaning it has a large number of endemic (local/native) plant species , and has “lost at least 70 percent of its original habitat.”
Dr Karmalkar’s paper will be published soon enough, I trust, and will give much more detail to those with deep knowledge about this kind of predictive mapping. For now I can only summarize, from a layperson’s perspective, the major points that I gleaned from his analysis. The PRECIS model works at two levels (atmospheric and on-the-ground) to try and predict the impact of climate changes on the selected global region.
Because PRECIS is measuring a part of the whole (a region of the earth, not the entire planet), it is a limited area model. This means a lot of the work of calculation has to occur at the boundaries – basically, at the edges or sides of the area. This involves figuring out the lateral boundary conditions (air and ground) and also the sea surface boundary conditions (especially its temperature). Dr Karmalkar ran two experiments (each one requiring seven months!) to confirm or deny the validity of PRECIS. Basically, do its results match up with reality? First, the baseline test involved validating whether the model could take information from the past and run through its algorithms to turn out a prediction matching what is actually happening now, in the present. He plugged in 31 years worth of observed data from ongoing measurements made in real time from 1960-1990. Given these values, the PRECIS model successfully generated a ‘prediction’ that accurately described current conditions of temperature and precipitation.
Changes in Seasonal Rainfall a Serious Concern
I highlight preciptation because I realized that I have been thinking naively about climate change in terms of temperature alone, but it is the combined effect of increasing temperature with changes in amounts of precipitation that is of serious concern. PRECIS simulates surface air temperature correctly, although there was a long discussion about differing warm- and cold-biases of the comparison data sets – CRU and NARR – at low and high elevations. The PRECIS results seem to highlight these biases. Perhaps this information will help designers improve the modeling. Nonetheless, Dr Karmalkar and his advisors agreed, “despite the challenges of a topographically complex region, PRECIS is not doing a bad job simulating temperature.” However, it is the annual cycle of precipitation that most defines the climate of Central America. Historically, there have been two rainy seasons generating peaks of rainfall in June, and again in September-October, with a bit of a dip in-between (July-August).
PRECIS is underestimating the wet season by 40-50%. A higher resolution model will help improve the simulation, and there may be a problem with how the model simulates storms. There are many interacting variables in this dynamic system, including mean annual sea level pressure, the subtropical high pressure systems (Atlantic and Pacific), low pressure in the eastern Atlantic NASH (North Atlantic Subtropical High) which defines the direction and speed of trade winds that carry the precipitation, effects from the Borealis force, sea surface temperature, and low level circulation of the atmosphere modified by the topography (mountains, valleys and such).
Comparing the Baseline and a Future Scenario
Once the baseline is established as accurate, its trajectory is run out to a point in the future without changing anything. If things were to continue only along the path that has already been created (nothing added, nothing taken away), then a certain climate can be projected to the end of the 21st century. To actually get at prediction, that extension of the baseline has to be compared with a possible projected future which includes changes we can anticipate (such as percent increase in greenhouse gasses – increasing at a rate of 3% a year since 2000 – more than double the rate in the 1990s).
There is an official Intergovernmental Panel on Climate Change that created four different possible scenarios. Dr Karmalkar picked the scenario called A2, which comes with an associated “storyline” – the context of human activity that makes the numbers used in the scenario plausible. The A2 storyline is conservative: of the four choices it is the one that seems the most “like” the way our world really is, now:
…a very heterogeneous world with continuously increasing global population and regionally oriented economic growth that is more fragmented and slower than in other storylines.
In this story about our possible future, economic values outweigh environmental values, and regional development is pursued more than global strategies.
“There’s a cockroach.”
It is the difference between the two tests – the baseline and the potential scenario – that generates the actual prediction. The finding shows temperature becoming higher and the distribution narrower: the future “lies well outside the present day” and “that,” says Dr Karmalkar, “is a significant result.” Remember that long discussion about bias? The results for all regions show a cold bias – which means (if I understood this correctly), that the prediction itself is conservative, i.e., that the reality could well be worse than these particular results predict. Warming in Central America is higher than the global average. Not only this, but the wet and dry seasons in Central America are going to be seriously effected. The model isn’t doing as well with precipitation as it is with temperature, but – even limping – what it suggests is grim. Basically, amounts of rainfall during the wet season are going to decrease, some areas might even lose one of the rainy seasons entirely. In other areas, perhaps the second wet season will be extended and last longer, enabling a small increase in precipitation, but the overall loss of rainfall over the sea will trigger other effects, shifting pressure systems, decreasing sea level pressure and strengthening trade winds – all of which will decrease precipitation.
It gets worse. Dr Karmalkar did not say that. He would not. He represented the science calmly, engaging an impressive display of slide jujitsu by answering every question posed during the defense with a quick scroll through his hundred (or more) back-up slides, pulling up the exact one to respond with precision to every query.
One of the most important sources of precipitation in Central America comes from clouds. The landscape includes tall mountains that touch the clouds: moisture condenses directly onto the vegetation. (This is where the Golden Toad used to live.) Twenty to 22% of the total annual precipitation in Costa Rica comes from this direct source of moisture. Clouds form as a function of relative humidity, which is a function of temperature and pressure. Can you guess? The temperature goes up, which draws the ‘ceiling’ of relative humidity up too. Clouds no longer form at the usual altitude, but higher up. Bye bye horizontal precipitation. What killed the Golden Toad? Possibly a phenomenon called moisture stress.
No Time to Lose
Again, this is my voice, not Dr Karmalkar’s. When pressed by his committee whether “it is appropriate at this point to press the alarm and get the word out to conservation organizations and such?” Dr Karmalkar responded:
“Yes, we do have enough information to, maybe not press the alarm, but enough to say that something needs to be done…the Golden Toad disappeared in 1989, its population dramatically declined after the El Nino phase of 1986-87. If you look at the temperature anomalies of El Nino, they are only of a degree or so. If one degree of change is effecting the species in the area, then certainly four degrees warming is definitely large.
One of the other important things is that species do adapt to changes in climate. There are cases where plant species have migrated upslope, but that’s constrained by topography. In some cases, I talked of the cloud base heights going up, but another problem is deforestation, which has led to an increase in surface sensitive heat flux. Land surface use alone can drive cloud bases even higher than the highest mountain peak.
We do have information to make the case that climate change of this magnitude might be serious.”