Monthly Archives: January 2006

More on Urban Temperatures

A very interesting NASA study has been reported entitled Keeping New York City “Cool” is the Job of NASA’s “Heat Seekers”

Thus study illustrates that the González et al tropical study that was discussed on the weblog on January 29th, also applies to midlatitude cities. The NASA study also shows that the deliberate modification of the urban landscape can alter the temperatures in this area.

Excerpts from the NASA report state,

“The ‘heat is on’ in New York City, whether it’s summer or winter. This is due to a phenomenon called the urban heat island effect that causes air temperatures in New York City and other major cities to be warmer than in neighboring suburbs and rural areas. And, in a big city, warmer air temperatures can impact air quality, public health and the demand for energy. “

‘We need to help public officials find the most successful ways to reduce the heat island effect in New York. With ever-increasing urban populations around the world, the heat island effect will become even more significant in the future,’ said Stuart Gaffin, an associate research scientist at Columbia University, New York, and a co-author of the new NASA study. ‘The summertime impacts are especially intense with the deterioration of air quality, because higher air temperatures increase ozone. That has health effects for everyone. We also run an increased risk of major heat waves and blackouts as the heat island effect raises demand for electricity.’

“In large cities, land surfaces with vegetation are relatively few and are replaced by non-reflective, water-resistant surfaces such as asphalt, tar and building materials that absorb most of the sun’s radiation. These surfaces hinder the natural cooling that would otherwise take effect with the evaporation of moisture from surfaces with vegetation. The urban heat island occurrence is particularly pronounced during summer heat waves and at night when wind speeds are low and sea breezes are light. During these times, New York City’s air temperatures can rise 7.2 degrees F higher than in surrounding areas. “

‘We found that vegetation is a powerful cooling mechanism. It appears to be the most effective tool to reduce surface temperatures,’ Gaffin said. ‘Another effective approach is a man-made approach to cooling by making very bright, high albedo, or reflected light, on roof tops. These light-colored surfaces, best made using white coatings, reflect the sun’s light and thereby, its heat. Interestingly, more area is available to create the lighter surfaces than to add vegetation in a city such as New York.'”

There are two cavaets to t his study, however. First, while the planting of vegetation can reduce the surface air temperature from what it otherwise would be, the addition of water vapor from transpiration can increase the humidity. This can make summer days more stressful as the heat index is elevated (e.g. see Segal, M. and R.A. Pielke, 1981: Numerical model simulation of human biometeorological heat load conditions – summer day case study for the Chesapeake Bay area. J. Appl. Meteor., 20, 735-749.).

Secondly, if the vegetated surface is darker, the solar insolation that is received at the surface will be greater than in the absence of this surface type. The result would be greater heat added to the surface, even though a fraction of the heat would be involved with the transpiration of water vapor. The need to account for the diverse consequences of land surface change for climate manipulation is discussed in Pielke Sr., R.A., 2001: Carbon sequestration — The need for an integrated climate system approach. Bull. Amer. Meteor. Soc., 82, 2021.

With these cavaets, however, the NASA study provides an effective summary of how we can positively alter the local climate for the benefit of society. The research group at the Lawrence Berkeley Laboratory directed by Hashem Akbari
is a leader in the investigation of such urban climate mitigation.

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More Evidence for the Diversity of Climate Forcings by Aerosols

A very important research paper has appeared with respect to the effect of aerosols within the climate system. The paper by A. Khain , D. Rosenfeld, and A. Pokrovsky entitled “Aerosol impact on the dynamics and microphysics of deep convective clouds”

includes the following conclusion,

“the ‘aerosol effect’ on precipitation can be understood only in combination with the ‘dynamical effect’ of aerosols. Simulations allow us to suggest that aerosols, which decrease the precipitation efficiency of most single clouds, can contribute to the formation of very intensive convective clouds and thunderstorms (e.g. squall lines, etc.) accompanied by very high precipitation rates. Affecting precipitation, net atmospheric heating and its vertical distribution, as well as cloud depth and cloud coverage, atmospheric aerosols (including anthropogenic ones) influence atmospheric motions and radiation balance at different scales, from convective to, possibly, global ones.â€?

The full abstract reads,

“Mechanisms through which atmospheric aerosols affect cloud microphysics, dynamics and precipitation are investigated using a spectral microphysics two-dimensional cloud model. A significant effect of aerosols on cloud microphysics and dynamics has been found. Maritime aerosols lead to a rapid formation of raindrops that fall down through cloud updraughts increasing the loading in the lower part of a cloud. This is, supposedly, one of the reasons for comparatively low updraughts in maritime convective clouds. An increase in the concentration of small cloud condensation nuclei (CCN) leads to the formation of a large number of small droplets with a low collision rate, resulting in a time delay of raindrop formation. Such a delay prevents a decrease in the vertical velocity caused by the falling raindrops and thus increases the duration of the diffusion droplet growth stage, increasing latent heat release by condensation. The additional water that rises to the freezing level increases latent heat release by freezing. As a result, clouds developing in continental-type aerosol tend to have larger vertical velocities and to attain higher levels.

The results show that a decrease in precipitation efficiency of single cumulus clouds arising in microphysically continental air is attributable to a greater loss of the precipitating mass due to a greater sublimation of ice and evaporation of drops while they are falling from higher levels through a deep layer of dry air outside cloud updraughts. By affecting precipitation, atmospheric aerosols influence the net heating of the atmosphere. Simulations show that aerosols also change the vertical distribution of latent heat release, increasing the level of the heating peak.
Clouds arising under continental aerosol conditions produce as a rule stronger downdraughts and stronger convergence in the boundary layer. Being triggered by larger dynamical forcing, secondary clouds arising in microphysically continental air are stronger and can, according to the results of simulations, form a squall line. The squall line formation was simulated both under maritime (GATE-74) and continental (PRE-STORM) thermodynamic conditions. In the maritime aerosol cases, clouds developing under similar thermodynamic conditions do not produce strong downdraughts and do not lead to squall line formation.

Thus, the ‘aerosol effect’ on precipitation can be understood only in combination with the ‘dynamical effect’ of aerosols. Simulations allow us to suggest that aerosols, which decrease the precipitation efficiency of most single clouds, can contribute to the formation of very intensive convective clouds and thunderstorms (e.g. squall lines, etc.) accompanied by very high precipitation rates. Affecting precipitation, net atmospheric heating and its vertical distribution, as well as cloud depth and cloud coverage, atmospheric aerosols (including anthropogenic ones) influence atmospheric motions and radiation balance at different scales, from convective to, possibly, global ones.â€?

This study provides support for the 2005 National Research Council conclusion that

“Several types of forcings—most notably aerosols, land-use and land-cover change, and modifications to biogeochemistry—impact the climate system in nonradiative ways, in particular by modifying the hydrological cycle and vegetation dynamics. Aerosols exert a forcing on the hydrological cycle by modifying cloud condensation nuclei, ice nuclei, precipitation efficiency, and the ratio between solar direct and diffuse radiation received.â€?;

and that we need to,

“Improve understanding and parameterizations of aerosol-cloud thermodynamic interactions and land-atmosphere interactions in climate models in order to quantify the impacts of these nonradiative forcings on both regional and global scales.â€?

The Khain et al paper is a major contribution to this goal, as well as further showing the complex interactions within the climate system which makes multi-decadal prediction a much more challenging endeavor than is captured by the IPCC perspective.

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Do Urban Areas have Larger Long term Temperature Trends than Other Locations?

A paper that appeared in EOS in October 2005 (subscription required) entitled “Urban Heat Islands Developing in Coastal Tropical Cities” by González et al is very relevant to the subject of long term surface temperature trend analyses such as reported by GISS and other groups. This paper indicates that the trends in surface temperatures in growing tropical urban locations are quite large. The paper states with respect to San Juan, Puerto Rico that,

“A recent climatological analysis of the surface temperature of the city has revealed that the local temperature has been increasing over the neighboring vegetated areas at a rate of 0.06 C per year for the past 30 years. This is a trend that may be comparable to climate changes induced by global warming”.

This study contradicts that of the Parker 2004 Nature paper entitled “Large-scale warming is not urban” and the Journal of Climate regional study of Peterson 2003 entitled “Assessment of urban versus rural in situ surface temperatures in the contiguous US: No difference found”. These later two studies were applied in the 2006 CCSP Report “Temperature Trends in the Lower Atmosphere:
Steps for Understanding and Reconciling Differences” to demonstrate the robustness of the global surface temperature trend analyses. The neglect of the conclusions of the González et al EOS paper (which was published prior to the completion of the CCSP Report), represents yet another example of its completion as an advocacy document in support of a particular limited perspective on surface and tropospheric temperature trends (see also my Public Comment on this CCSP Report).

Moreover, since such a large urban trend, if representative of other coastal tropical cities, instead of meaning that “This is a trend that may be comparable to climate changes induced by global warming”, indicates that the “global warming” signal itself, as diagnosed by surface temperatures, has a warm bias, when interpolated to a larger grid analysis area as a result of these large urban temperature trends.

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Climate Model Problems in Representing Near-Surface Temperatures at Night

An article in the November 1, 2005 Integrated Land Ecosystem-Atmosphere Processes Study (iLEAPS) Newsletter by Professor Bert Holtslag of Wageningen University in the Netherlands entitled “Stable boundary layers and land surface climateâ€? summarizes serious difficulties in the accurate representation of near surface processes at night, including temperature. This topic was presented with further updates by Professor Holtslag at the iLEAPS meeting this week in Boulder, Colorado.

The abstract states,

“GABLS refers to the GEWEX Atmospheric Boundary Layer Study. The project aims to improve the understanding and the representation of the atmospheric boundary layer in regional and large-scale climate models. Results of a recent GABLS model intercomparison highlighted large model errors due to an inadequate representation of small-scale and near surface processes. These errors effect prediction of local and regional representations of land-atmosphere exchange and may impact on global scale climate studies as well.â€?

The identification of this problem with climate models provides further support for the conclusion made in the January 23 2006 weblog that,

“This raises the possibility that those GCMs that appear to accurately represent global average temperature trends over recent decades may be obtaining results that look right when compared to data, but for the wrong physical reasons. If so, this would call into question their ability to accurately predict the future evolution of the climate system.â€?

There are significant remaining uncertainties in the modeling of long-term surface temperature trends, as well as uncertainties in the accurate observational monitoring of these trends.

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Why there is a Warm Bias in the Existing Analyses of the Global Average Surface Temperature

Readers of this weblog know that there have been comments on the warm bias that we have identified, as reported in Matsui and Pielke, GRL, 2005, with respect to the global analysis of surface temperature trends. This is an important issue as this climate metric is used as an icon to communicate the concept of global warming to policymakers. The abstract of the Parker 2004 Nature paper , for example, stated that the

“Controversy has persisted over the influence of urban warming on reported large-scale surface-air temperature trends. Urban heat islands occur mainly at night and are reduced in windy conditions. Here we show that, globally, temperatures over land have risen as much on windy nights as on calm nights, indicating that the observed overall warming is not a consequence of urban development.â€?

Parker 2004 has been used as evidence to argue that the global surface temperature trends are robust (e.g. CCSP, 2006). In the Matsui and Pielke paper, we show, however, that trends of surface air temperature should not be expected to have the same values for the different sets of days used in the Parker paper. Based on well understood concepts of boundary level meteorology, because Parker found similar trends, there necessarily must be some error in Parker’s analysis. For those unfamiliar with boundary layer meteorology, the reason for this is that minimum temperatures on calm nights should in fact show a larger warming trend than on windy nights (explained below), and not the identical trends reported by Parker. We were motivated to look at this subject because of the obvious inconsistency in the Parker results, and what we found has much broader implications for the long-term surface temperature record.

Studies of the lower levels of the atmosphere (lowest tens of meters) show that it cools at night when winds do not move warm air into the area. This cooling occurs as heat is lost to space. For this reason, minimum daily temperatures typically occur near sunrise, due to cooling overnight. The nighttime cooling varies with height. With light winds, the cooling is greater near the surface and less aloft, while with stronger winds, which are associated with greater mixing of the air above a particular location, the cooling rate is more uniform with height. Light and strong winds can be documented at a particular location from observed wind data.

The rate of heat loss to space is dependent on several factors, including cloudiness and the local atmospheric concentrations of carbon dioxide and of water vapor. Under cloudy conditions, the cooling is much less. Similarly, an atmosphere with higher concentrations of the greenhouse gases, CO2 and H2O, also reduces the cooling at night. Consequently, if there is a long-term trend in greenhouse gas concentrations or cloudiness it will introduce a bias in the observational record of minimum temperatures that will necessarily result in a bias in the long-term surface temperature record.

Because of changes to the atmosphere over the past century, there are several reasons why we should expect the nighttime cooling in the lower atmosphere to have been reduced. One reason for this is that carbon dioxide concentrations have increased, such that the local effect of greenhouse gas concentrations on temperature measurements is larger. Also, an increase of cloudiness has been reported which has the effect of reducing nighttime cooling. An increase in water vapor content in the lower atmosphere would also reduce the cooling rate at night.

Our paper shows that in such circumstances where nighttime cooling is reduced systematically over time, i.e., under trends of greater atmospheric greenhouse gases or an increase in cloudiness, the resulting effect will be to increase minimum temperatures from what they would have been absent the reduced nighttime cooling. This increase in minimum temperatures is greater on nights with light winds than nights with strong winds, due to the mixing of air, and can be on the order of 1 degree C in the lowest 10m above the ground. Minimum daily temperatures are of course important because they are used as input to calculate the daily temperatures that comprise the long-term surface temperature record.

When there is a long-term trend of a reduction in nighttime cooling, then when temperature data are collected, the combination of all of the minimum temperatures on light and strong wind nights will result in an overstatement of warming trends by tenths of a degree. (Note that this assumes that the overall reduction of nighttime cooling such as due to more cloudiness over time and/or increases in the atmospheric concentration of carbon dioxide and/or water vapor is on the order of 1 watt per meter squared. Based on the IPCC, 2001 findings, this is a reasonable estimate of the change over the recent decades in the atmospheric radiative forcing).

What this means is that because (a) the land surface temperature record does in fact combine temperature measurements of light wind and windy nights and (b) there has been a reduction in nighttime cooling, the long-term temperature record may be contaminated by a warm bias that accentuates the observed trend of warmer temperatures. Such a bias would be of similar or larger magnitude to those biases recently discussed in the context of global satellite measurements of temperature. The reduction in nighttime cooling that leads to this bias may indeed be the result of human interference in the climate system (i.e., local effects of increasing greenhouse gases or human effects on cloud cover), but through a causal mechanism different than that typically assumed.

This effect results from a systemic microclimate effect in temperature data which are present in the global temperature record, but are unaccounted for in current analyses. This raises the possibility that those GCMs that appear to accurately represent global average temperature trends over recent decades may be obtaining results that look right when compared to data, but for the wrong physical reasons. If so, this would call into question their ability to accurately predict the future evolution of the climate system.

The broader implications of Matsui and Pielke (2005), which will be well understood by anyone with an understanding of the physics of the lower atmosphere, should cause consternation among anyone who uses the global temperature trend record for scientific or policy purposes. As we have emphasized here (as have others, such as Hansen, Levitus, Barnett, Willis) a more meaningful metric than global average temperature to assess global warming is ocean heat content.

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The Need to Better Assess Uncertainty in Climate Models

The November 2005 issue of GEWEX News (GEWEX is the Global Energy and Water Cycle Experiment) has an excellent article by T. Palmer of the ECMWF entitled “Ensemble Weather and Climate Predictionâ€?.

His article states “the representation of model uncertainty is a developing subjectâ€?.

This is an important conclusion that needs to be widely recognized by the climate community.

He identifies three currently used methods to assess uncertainty including multi-model ensembles, perturbed-parameter ensembles, and stochastic physics. Multi-model ensembles have been utilized in multi-decadal retrospective predictions, such as in the CCSP report “Temperature Trends in the Lower Atmosphere: Understanding and Reconciling Differencesâ€? . However, the use of perturbed-parameter ensembles (where uncertainties in the tunable parameters within model parameterizations are used to run the models with different values of these paramters), and stochastic physics (where the parameterizations include a statistical component) have not been completed with climate models. Of course, we also need to include all of the first order climate forcings and feedbacks, which, as we have discussed several times on this weblog, are not yet in the mult-decadal climate prediction models.

His article provides encouragement for model uncertainty assessments by the climate modeling community

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Effect on Surface Temperature Trends Due to Local Human Alteration of the Landscape

A new paper by John Christy, William Norris, Kelly Redmond and Kevin Gallo, in press with the Journal of Climate, entitled “Methodology and Results of Calculating Central California Surface Temperature Trends: Evidence of a Human-Induced Climate Change” offers important new insight to the role of landscape change in climate and in the interpretation of surface air temperature changes. The abstract of the paper reads,

“A procedure is described to construct time series of regional surface temperatures and is then applied to interior Central California stations to test the hypothesis that century-scale trend differences between irrigated and non-irrigated regions may be identified. The procedure requires documentation of every point in time at which a discontinuity in a station record may have occurred through (a) the examination of metadata forms (e.g. station moves) and (b) simple statistical tests.
From this we define “homogeneous segments” of temperature records for each station. Biases are determined for each segment relative to all others through a method employing mathematical graph theory. The debiased segments are then merged, forming a complete regional time series. Time series of daily maximum and minimum temperatures forstations in the irrigated San Joaquin Valley (Valley) and nearby non-irrigated Sierra Nevada Mountains (Sierra) were generated for 1910-2003. Results show that 20th century Valley minimum temperaturesare warming at a highly significant rate in all seasons, being greatest in summer and fall ( > +0.25 °C decade-1). The Valley trend of annual mean temperatures is +0.07 ±0.07 °C decade-1. Sierra summer and fallminimum temperatures appear to be cooling, but at a less significantrate, while the trend of annual mean Sierra temperatures is an unremarkable -0.02 ±0.10 °C decade-1. A working hypothesis is that the relative positive trends in Valley minus Sierra minima ( > 0.4 °C decade-1 for summer and fall) are related to the altered surface environment brought about by the growth of irrigated agriculture,essentially changing a high-albedo desert into a darker, moister,vegetated plain.”

The University of Alabama at Huntsville (UAH) has released a press release on January 18 on this paper (URL). Extracts from the news release state

“A two-year study of San Joaquin Valley nights found that summer nighttime
low temperatures in six counties of California¹s Central Valley climbed
about 5.5 degrees Fahrenheit (approximately 3.0 C) between 1910 and 2003.
The study’s results will be published in the Journal of Climate.

The study area included six California counties: Kings, Tulare, Fresno,
Madera, Merced and Mariposa.

While nighttime temperatures have risen, there has been no change in summer
nighttime temperatures in the adjacent Sierra Nevada mountains. Summer
daytime temperatures in the six county area have actually cooled slightly
since 1910. Those discrepancies, says Christy, might best be explained by
looking at the effects of widespread irrigation.

Since the early 20th Century irrigation has helped to convert much of
California’s Central Valley desert — including more than two million acres
in the study area’s six counties — into a dark, moist, vegetated plain.

Irrigation has not spread into the nearby mountains, Christy said, and that
might be why summer nighttime temperatures there haven’t warmed.

With help from UAH’s William Norris, Dr. Kevin Gallo, a NOAA scientist at
the U.S. Geological Survey’s National Center for Earth Resources Observation
and Science in Sioux Falls, S.D., and Kelly Redmond at the Western Regional
Climate Center in Reno, NV, Christy spent two years studying the valley’s
climate record, hand-entering into the database information from 1,600 pages
of daily temperature reports back to 1887 from some stations. He ended up
with 18 valley and 23 mountain stations to study.

The conflicting temperature trends in the valley and the mountains reduce
the likelihood that the valley’s warmer summer nights might be caused by
large-scale or global climate change due to enhanced greenhouse gases,
especially carbon dioxide, in the atmosphere, Christy said. ‘If this was
related to large-scale climate change, you would expect all elevations to be
affected.’

Computer models used to forecast climate change also typically predict that
in California the effects of global warming due to increased carbon dioxide
levels should warm temperatures in the Sierra Nevada mountains faster than
in the nearby valleys. The UAH study, however, found that from 1910 to 2003
night and daytime temperatures in the nearby mountains did not climb.”

The careful analysis of the data to minimize biases, as well as the protocol of comparing a set of data from valley and mountainous locations provides a robust assessment of how landscape processes affect the surface temperature trends. Landscape processes, with respect to how the land surface temperatures have been altered over time, has been a neglected issue in assessments such as the IPCC.

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