Monthly Archives: July 2005

Did Denver Tie Its All-Time Measure Heat Record on July 21, 2005?

The news in Colorado is highlighting the 105°F temperature recorded at Denver International Airport as tieing the all-time Denver record. However, the Airport site was established in 1995. Thus, we do not know if this was a long-term temperature record at this site. Other sites in eastern Colorado were hot, but they did not all exceed an all-time record (the Fort Collins observing site, for example, did not even reach 100°F yesterday, although it was still hot!). An accurate media perspective of this “all-time record” value is given in this Rocky Mountain News article.

This heat wave again illustrates why we also need to monitor moist enthalpy as discussed in the posting of July 18th . The dewpoint temperatures were in the upper 20s F, while the temperature was in above 100°F at the airport. The actual heat content of the air should also be included when discussing heat waves.

The answer to the question is that the official site for the Denver measurement tied its all-time record temperature. However, the location of this official measurement has moved over time, so we really do not know whether it really is the day with the highest temperature for the city in general. At the Colorado Climate Office, we will collect the data from around the state to place this heat wave in context (we expect to report on this in August after all of the data arrives from the cooperative weather observers). In terms of heat in the air (moist enthalpy) we recommend that this important climate metric be also tracked to really determine what is the hottest day.

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Water Vulnerability – A Topic for the Next G8?

The recent G8 meeting will be remembered, amongst the other items discussed, for the unfortunate London bombings and the somewhat lame climate change initiative that resulted after all the fanfare about this being the place to highlight the issue of the century — climate change.

But are we really correct in calling climate change the only critical issue we are dealing within the Earth system today? Clearly climate change is an issue that needs a framework and policy developed by the global community to help solve some fundamental issues such as reduction in GHG emissions, technology adaptation, and development of scientific concepts to sequester GHGs, etc.

It is important that the scientific community demonstrate its ability and propensity to adapt a broader perspective to encompass a more holistic perspective that considers the vulnerability of the Earth’s resources and possible adaptability and mitigative strategies. It is then feasible that the disconnect between science and the compromises that policymakers and the populace have to make in reaching the decisions between a myriad of choices in abating climate change possible.

The vulnerability of water resources as a global issue is indeed critically poised even as the world debates climate change. There is growing evidence (Douglas et al. 2005, Nat. Haz, in review) that between 1990 and 2025 the number of people living in countries without adequate water is projected to rise from 131 million to 817 million. India is supposed to fall into the water stress category long before 2025 (Shiva, 2002).

Let’s continue with the example of India to illustrate a few areas where the hydrological vulnerability problem lie. Climate change can contribute to the variations in the natural water cycle and cause stress on the water resources. Over and beyond that, there are significant societal issues which have more direct impacts on the water resources (and vice versa). For instance, the increasing trend in privatizing water sources has played a daunting role in the inequity of water access. Private ownership, rather than collective sharing, has left many villagers paying exorbitant rates for water (something that is nearly impossible to afford for sustenance farmers) or spending hours locating alternate water sources. As water availability decreases, malnutrition, disease, and infant mortality increase.

Another problem that plagues communities that are stressed with the difficult choice between water vulnerability and economic choices, is related to the commodity returns. For instance, rural India is shifting from farming food crops to cash crops. Sainath notes (1999) in many areas water intensive sugarcane is replacing traditional yield such as wheat. Sugarcane requires ten times as much water as wheat!

As water needs increase, more resources are utilized and consumption goes well beyond the recharge potential of water sources.
Urban areas are not immune to water vulnerability either. Manufacturing requires water while industrial waste pollutes rivers and water sheds. Villagers migrate to cities due to water shortages, land and water ownership issues and lack of economic opportunity, and increase the burden on the already overpopulated urban areas. Excess population leads to water scarcity since the resources remain near constant. Often improper sanitation facilities add to the contamination of water, leaving even less water for human consumption.
Note that the water vulnerability is not only a problem for the developing world. In the United States, wells have dried up from water depletion in places like Texas, Oklahoma, and Kansas (Brown, 2003).

So whether G8 faces up to the fact that water resource vulnerability is a severe environmental disaster the world is facing or not — the rural and urban communities across the world will live through a decade which will make or break the social infrastructure or what it can develop into or what it can provide to its population.

Brown, L. (2003) World Creating Food Bubble Economy Based on Unsustainable Use of Water,
Douglas E., D. Niyogi, S. Frolking, J.B. Yeluripati, R. A. Pielke Sr., N. Niyogi, C. J. Vörösmarty, U.C. Mohanty (2005) Changes in moisture and energy fluxes due to agricultural land use and irrigation in the Indian Monsoon Belt, J. Natural Hazards (Monsoon Special Issue), in review.
Sainath, P. (1999) Everybody Loves a Good Drought, Headline Book Publishing, London, GB. pp. 255-292.
Shiva, V. (2002) Water Wars, South End Press, Cambridge, MA, pp. 1, 20

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What Does Moist Enthalpy Tell Us?

In our blog of July 11, we introduced the concept of moist enthalpy (see also Pielke, R.A. Sr., C. Davey, and J. Morgan, 2004: Assessing “global warming” with surface heat content. Eos, 85, No. 21, 210-211. ). This is an important climate change metric, since it illustrates why surface air temperature alone is inadequate to monitor trends of surface heating and cooling. Heat is measured in units of Joules. Degrees Celsius is an incomplete metric of heat.

Surface air moist enthalpy does capture the proper measure of heat. It is defined as CpT + Lq where Cp is the heat capacity of air at constant pressure, T is air temperature, L is the latent heat of phase change of water vapor, and q is the specific humidity of air. T is what we measure with a thermometer, while q is derived by measuring the wet bulb temperature (or, alternatively, dewpoint temperature).

To illustrate how important it is to use moist enthalpy, we can refer to the current heat wave in the southwest United States. The temperatures in Yuma, Arizona, for example, have reached 110°F (43.3°C), but with dewpoint temperatures around 32°F (0°C). In terms of moist enthalpy, if the temperature falls to 95°F (35°C) but the dewpoint temperature rises to 48°F, the moist enthalpy is the same. Temperature by itself, of course, is critically important for many applications. However, when we want to quantify heat in the surface air in its proper units in physics, we must use moist enthalpy.

In terms of assessing trends in globally-averaged surface air temperature as a metric to diagnose the radiative equilibrium of the Earth, the neglect of using moist enthalpy, therefore, necessarily produces an inaccurate metric, since the water vapor content of the surface air will generally have different temporal variability and trends than the air temperature.

There are quite a few other issues with using the global-averaged surface temperature to characterize climate change (see NRC 2005, Radiative Forcing of Climate Change: Expanding the Concept and Addressing Uncertainties). The realization that temperature is an incomplete measure of heat adds another problem to its use.

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More On The Arctic; Have The Coldest Temperatures In The Mid-Troposphere Warmed?

In the July 15th blog, the issue of Arctic sea ice melting was discussed. The issue of tropospheric temperature trends has also been investigated. In two papers (see Chase et al., 2002: A proposed mechanism for the regulation of minimum midtropospheric temperatures in the Arctic. J. Geophys. Res., 107(D14), 10.10291/2001JD001425 and Tsukernik et al., 2004: On the regulation of minimum mid-tropospheric temperatures in the Arctic. Geophys. Res. Lett., 31, L06112, doi:10.1029/2003GL018831), we investigated whether the area coverage of the coldest temperatures at 500 mb (which is in the mid-troposphere) in the Northern Hemisphere winter has decreased between 1950 and 1998 (it had not as shown in the first of these two papers; see Figure 1 in that paper).

The motivation of this study was a discussion in front of 500 mb weather maps by Professor Ben Herman and me during my visit at the University of Arizona. We both had noted that the coldest temperatures (-40°C to -45°C) were typically reached in November, rather than continuing to become colder for the rest of the winter. We found there is a feedback between the ocean sea surface temperatures and the temperatures at 500 mb. Even though the air at 500 mb could become colder for short times over large continental areas such as Siberia, the air is advected often enough over ice-free ocean (but near freezing) that cumulus convective mixing results in a vertical temperature lapse rate that is nearly moist adiabatic. This produces 500 mb temperatures that are close to -45°C.

This self-regulation of the climate system indicates that the Arctic troposphere, in terms of the areal average of the coldest mid-tropospheric temperatures, is more resilient to change than expressed in the Arctic Climate Impact Assessment (ACIA) report. This is another set of peer-reviewed papers that was ignored in the ACIA study.

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Is Arctic Sea Ice Melting?

In the 2005 Arctic Climate Impact Assessment (ACIA) report, it was stated that:

“Over the past 30 years, the annual average sea-ice extent has decreased by about 8%… and the melting trend is accelerating”, and that “Sea-ice extent in summer has declined more dramatically than the annual average, with a loss of 15-20% of the late-summer ice coverage.”

They do caveat these statements by stating that “There is also significant variability from year to year.”

My AT786 class examined this issue. In 2004, I published a paper with Glen Liston, Bill Chapman, and Dave Robinson which concluded for the period 1973-2002 that “The sea-ice decline from 1973 is about 6%, while from 1980 the decrease to 2002 is about 3%…….the 1980-2002 observed decrease is less then the simulated decrease of actual sea-ice areal coverage reported in Global Warming and Northern Hemisphere Sea Ice Extent by Vinnokov et al. 1999. This paper was a follow up to a paper in 2000 by myself with Glen Liston and Alan Robock. One immediate question is why were these two papers not cited in the ACIA report?

Our class then examined the current state of Arctic sea ice. What is clearly evident in the data as of June-July 2005, is that Arctic sea-ice coverage is close to its long-term mean at this time of the year. After being well below average this past winter, the spring melt was slower than average. As discussed in the two papers I cite above, in terms of a warming feedback to the atmosphere through the radiative effect with respect to sea-ice coverage (the ice-albedo effect), it is the summer spring and summer areal coverage that is most critical (since in the winter with the long nights, there is little if any sunlight to reflect back into space).

The multi-year long-term trend and thickness of Arctic sea ice has also been used to claim the sea ice is melting. Indeed, this may be the case, although the data are more difficult to quantify in terms of long-term variability than areal coverage. Areal coverage, however, is the component of sea ice which has the most direct impact on the climate system through the ice-albedo feedback effect. As seen in these graphs, there is no clear trend since 1997. The melting trend is not accelerating. Moreover, a linear trend poorly captures the temporal behavior of this complex component of the climate system. If the sea-ice coverage returns to an earlier coverage, the clock is reset with respect to a linear trend.

Our conclusion is that the Arctic Systems Science report, which received so much media attention, significantly overstated the actual trends of Arctic sea-ice coverage.

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What Are Climate Models? What Do They Do?

Climate models are comprised of fundamental concepts and parameterizations of physical, biological, and chemical components of the climate system, expressed as mathematical formulations, and then averaged over grid volumes. These formulations are then converted to a programming language so that they can be solved on a computer and integrated forward in discrete time steps over the chosen model domain. A global climate model needs to include component models to represent the oceans, atmosphere, land, and continental ice and the interfacial fluxes between each other. Weather models are clearly a subset of a climate model (a discussion of mesoscale weather models is given in Pielke, R.A., Sr., 2002: Mesoscale meteorological modeling. 2nd Edition, Academic Press, San Diego, CA, 676 pp), where the basic framework of all scales of weather models is presented). On the global scale, it is very important to distinguish global atmospheric-ocean circulation models (AOGCMs) from global climate models. Global climate models need to include all important components of the climate system as discussed in a 2005 National Research Council report, while AOGCMs up the present have not.

There are three types of applications of these models: for process studies, for diagnosis and for forecasting.

Process studies: The application of climate models to improve our understanding of how the system works is a valuable application of these tools. In an essay, I used the term sensitivity study to characterize a process study. In a sensitivity study, a subset of the forcings and/or feedback of the climate system may be perturbed to examine its response. The model of the climate system might be incomplete and not include each of the important feedbacks and forcings.

Diagnosis: The application of climate models, in which observed data is assimilated into the model, to produce an observational analysis that is consistent with our best understanding of the climate system as represented by the manner in which the fundamental concepts and parameterizations are represented. Although not yet applied to climate models, this procedure is used for weather reanalyses (see the NCEP/NCAR 40-Year Reanalysis Project).

Forecasting: The application of climate models to predict the future state of the climate system. Forecasts can be made from a single realization, or from an ensemble of forecasts which are produced by slightly perturbing the initial conditions and/or other aspects of the model. Mike MacCracken, in his very informative response to my Climatic Change essay seeks to differentiate between a prediction and a projection.

With these definitions, the question is where does the IPCC and US National Assessment Models fit? Since the General Circulation Models do not contain all of the important climate forcings and feedbacks (as given in the aforementioned 2005 NRC report) the models results must not be interpreted as forecasts. Since they have been applied to project the decadal-averaged weather conditions in the next 50-100 years and more, they cannot be considered as diagnostic models since we do not yet have the observed data to insert into the models. The term projection needs to be reserved for forecasts, as recommended in Figure 6 in R-225.

Therefore, the IPCC and US National Assessments appropriately should be communicated as process studies in the context that they are sensitivity studies. It is a very convoluted argument to state that a projection is not a prediction. The specification to periods of time in the future (e.g., 2050-2059) and the communication in this format is very misleading to the users of this information. This is a very important distinction which has been missed by impact scientists who study climate impacts using the output from these models and by policymakers.

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The Globally-Averaged Surface Temperature Trend – Incompletely Assessed? Is It Even Relevant?

The globally-averaged surface temperature trend has been highlighted as an icon of climate change. For example, a meeting was held In Exeter, United Kingdom from Feb 1-3, 2005 entitled “Avoiding Dangerous Climate Change.” The focus on a globally-averaged temperature trend was clear in the emphasis at the meeting. The Hadley Centre brochure relevant to this meeting stated “Once a tolerable (i.e., non-dangerous) change has been determined – say in terms of a global temperature rise – we then have to calculate what this corresponds to in terms of tolerable greenhouse concentrations in the atmosphere.” The message is that a clear global surface temperature threshold exists over which there are dangerous effects on the climate system.

This perspective however, avoids discussing the real issue associated with long-term variability and changes in climate.

First, in the context of atmospheric circulation changes (which is, after all what produces our weather), it is the regional tropospheric temperature and humidity trends that are important, not a global average surface temperature A change in the globally-averaged surface, or even globally-averaged tropospheric, temperature are important primarily in the context of how this results in circulation changes. The globally-averaged surface temperature is a very poor metric to use to assess these circulation changes. The 2005 NRC report recognized this limitation in using globally-averaged surface temperatures. Secondly, with respect to even “global warming” the ocean heat content changes, rather than the surface temperature anomaly provides a more robust metric (see R-247).

With respect to the surface temperature itself, there are several issues with respect to the spatial representativeness of the trends that have been incompletely (or not at all) investigated. These are:

1. Poor microclimate exposure:
This is a land issue. The use of photographs to exclude questionable stations is obvious (and we are quite puzzled why anyone would not make this a high priority). The effect of poor exposure (which results in different site exposure depending on the wind direction) and changes in the site conditions over time have not been quantified. Our qualitative assessment based on the photographs that we have seen is that this it is likely to insert a warm bias for most sites.

2. Moist enthalpy:
This is both a land and an ocean issue. The use of the terms “warming” and “cooling” are being incompletely used when there is significant water vapor in the surface air (tropics and mid-latitude warm seasons, in particular). This will produce a warm bias when the air actually became drier over time, and a cool bias when the air becomes more humid over time. This effect has not been quantified with respect to how it influences regional and global surface temperature trends. It has been shown to be significant for individual sites.

3. Vertical lapse rate issues (paper in preparation):
The influence of different lapse rates, heights of observations and surface roughness have not been quantified. For example, windy and light wind nights should not have the same trends at most levels in the surface layer, even if the surface-layer averaged temperature trend was the same.

4. Uncertainty in homogeneity adjustments:
Time of observation, instrument changes, and urban effects have been recognized as important adjustments (see R-234) that are required to revise temperature trend information in order to produce improved temporal and spatial homogeneity. However, these adjustments do not report in the final homogenized temperature anomalies, the statistical uncertainty that is associated with each step in the homogenization process.

Thus even if the globally-averaged surface temperature was a particularly appropriate metric to assess climate change, there are issues on the robustness of this data set which have been overlooked. Our recommendation, however, is to deemphasize the globally-averaged surface temperature as a climate change metric and assess instead circulation changes as defined by tropospheric temperature and water vapor (and for the ocean, temperature and salinity) variability and trends.

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