New paper finds Urban Heat Island effect should not be 'considered exclusively a nighttime phenomenon anymore'

A paper published today in the Journal of Climate uses a new method comparing satellite and surface temperature observations to assess the Urban Heat Island [UHI] effect. The paper finds "UHI is stronger during the day and summer than during nighttime and winter," which is the opposite of the predictions of computer models and assumption of most climate scientists heretofore that UHI is a "nocturnal phenomenon."

From the discussion:

The UHI is evident from the radiative surface skin temperature field. There is  clear diurnal variation in UHIskin, with larger UHI intensity during daytime than during nighttime. There is also a seasonal variation in UHIskin, with a larger signal in summer than in winter. This seasonal variation corresponds to the seasonality of solar radiation, the vegetation growing cycle, and rainfall or soil moisture content.

UHIskin maximizes during the daytime. Therefore, we should not consider UHI exclusively a “nighttime phenomenon” anymore. Jin et al. (2005) suggested the possible physical mechanisms responsible for a stronger daytime UHI. The albedo is reduced in urban regions, partly due to urban canopy effect and partly due to new materials used in urban roads and buildings; consequently, more solar radiation is absorbed at the surface to warm it. In addition, surface emissivity is reduced because of the new materials used in the urban surface, leading to less longwave radiation leaving the surface. As a result, daytime UHI is stronger than that nighttime. Furthermore, urban regions reduce soil moisture and vegetation coverage, which further change the solar radiation redistribution      in terms of latent and sensible heat fluxes (e.g, Bowen ratio), and thus increases surface temperature. MODIS provides albedo data (Shaff et al. 2003), emissivity data (Jin and  Liang 2006), and vegetation data (Myneni et al. 1995), which can be further used to address these mechanisms.

Full paper here

Journal of Climate 2012 ; e-View

doi: http://dx.doi.org/10.1175/JCLI-D-11-00509.1

Developing an Index to Measure Urban Heat Island Effect Using Satellite Land Skin Temperature and Land Cover Observations

Menglin S. Jin*

Department of Meteorology and Climate Science, San José State University

Abstract

A new index of calculating the intensity of urban heat island effects (UHI) for a city using satellite skin temperature and land cover observations is recommended. UHI, the temperature difference between urban and rural regions, is traditionally identified from the 2-m surface air temperatures (i.e., the screen-level temperature, T_2m) measured at a pair of weather stations sited in urban and rural locations, respectively. However, such screen-level UHI is affected by location, distance, and geographic conditions of the pair of weather stations. For example, choosing a different pair of rural and city sites leads to a different UHI intensity for the same city, due to the high heterogeneity of the urban surface temperature. To avoid such uncertainty, satellite-observed surface skin temperature measurements (i.e., skin level, T_skin) is recommended to record UHI, known as skin-level UHI or UHI_skin. This new index has advantages of high spatial resolution and aerial coverage to better record UHI intensity than T_2m. An assessment of skin-level UHI from 10-years of the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) observations reveals that skin-level UHI has a strong UHI signal during day and night. In addition, there are significant diurnal and seasonal variations in skin-level UHI. Furthermore, the skin-level UHI is stronger during the day and summer than during nighttime and winter, respectively. This new index is important for more uniformly assessing UHIs over cities around the globe. Nevertheless, whether the seasonality and diurnal variations revealed in this work using skin-level UHI index is valid over desert cities, such as Phoenix, needs to be examined.

New Retreat from Global Warming Data by Australian Gov Bureau

Article by John O’Sullivan and Val Majkus (via email from John O'Sullivan)

Global warmers in full retreat as Aussie experts admit growing doubts about their own methods as new study shows one third of temperatures not reliable.

The Australian Bureau of Meteorology (BOM) admits it was wrong about urban heating effects as a professional statistical analysis by Andrew Barnham exposes a BOM claim that “since 1960 the mean temperature in Australia has increased by about 0.7 °C”; the BOM assertion has no empirical scientific basis.

Barnham, who spent 8 years working in emerging South Asian economies building high volume transaction processing systems, applied a high-tech statistical technique very different from an earlier well-publicized probe by fellow Aussie, Ken Stewart on his blog, Ken’s Kingdom.

Stewart grabbed headlines in what became known as the Australiagate controversy after his findings were featured on popular science blog, Watts Up With That. Stewart exposed dubious BOM adjustments to temperature data that bore little or no resemblance to actual or raw past temperatures.

Like Stewart, Barnham paid particular attention to BOM’s methodology in addressing what is known as the Urban Heat Island Effect (UHI), a proven phenomenon whereby thermometers measuring temperatures in towns and cities become unduly influenced by extra ‘background’ heating from buildings, road surfaces, machinery, etc. It’s in the UHI adjustments that the greatest discrepancies appear to lie.

New paper finds urban heat islands cause up to 44% of total recorded warming

A paper published today in the Journal of Geophysical Research finds that urban heat islands account for up to 44% of the recorded warming in cities in east China over the period of 1981-2007. An urban heat island is a metropolitan area which is significantly warmer than its surrounding rural areas. As extensively documented by the surfacestations.org project, poor siting of weather stations in the US near urban heat islands results in a false warming trend in which "9 of every 10 stations are likely reporting higher or rising temperatures because they are badly sited." This shows why Phil Jones was worried that the Chinese Meteorological Agency was not playing along to prop up the AGW fallacy by recording temperatures at airports (highly biased by the urban heat island effect) in favor of unbiased rural areas. Without knowledge of the urban heat island effects on a global basis, it is unknown how much of the claimed 0.7C rise in temperature since 1850 is simply an artifact of poor siting rather than actual warming. Alarmists including the IPCC dismiss the urban heat island effect as insignificant, but as this paper and many others show, the effect causes very significant upward biases in recorded temperatures.

Metropolises warmed ~1.4C compared to surrounding rural areas ~0.4C over the period 1981-2007

JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 116, D14113, 12 PP., 2011

Observed surface warming induced by urbanization in east China

Key Points:

The rapid urbanization has significant impacts on temperature over east China
A new method was developed to dynamically classify urban and rural stations
Comparison of the trends of UHI effects by using OMR and UMR approaches

Xuchao Yang et al

Monthly mean surface air temperature data from 463 meteorological stations, including those from the 1981–2007 ordinary and national basic reference surface stations in east China and from the National Centers for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) Reanalysis, are used to investigate the effect of rapid urbanization on temperature change. These stations are dynamically classified into six categories, namely, metropolis, large city, medium-sized city, small city, suburban, and rural, using satellite-measured nighttime light imagery and population census data. Both observation minus reanalysis (OMR) and urban minus rural (UMR) methods are utilized to detect surface air temperature change induced by urbanization. With objective and dynamic station classification, the observed and reanalyzed temperature changes over rural areas show good agreement, indicating that the reanalysis can effectively capture regional rural temperature trends. The trends of urban heat island (UHI) effects, determined using OMR and UMR approaches, are generally consistent and indicate that rapid urbanization has a significant influence on surface warming over east China. Overall, UHI effects contribute 24.2% to regional average warming trends. The strongest effect of urbanization on annual mean surface air temperature trends occurs over the metropolis and large city stations, with corresponding contributions of about 44% and 35% to total warming, respectively. The UHI trends are 0.398°C and 0.26°C decade−1. The most substantial UHI effect occurred after the early 2000s, implying a significant effect of rapid urbanization on surface air temperature change during this period.

Another Junk Science Article confusing UHI, AGW, and Weather

Another alarmist junk science article, Manhattan Heat Waves Sign of City Scorchers to Come, confuses the urban heat island effect (UHI), "anthropogenic" global warming (AGW), and seasonal weather to spin a tale of more frequent and intense "city scorchers to come." The article begins by correctly noting the urban heat island effect (UHI) is the reason for the increase of 10-15°F in nighttime temperatures in Manhattan compared to outlying areas. Dr. Kevin Trenberth, eternal seeker of the "missing heat," is stated to be surprised at the magnitude of this "huge" effect, and perhaps this explains why he and his colleagues have previously dismissed the findings of Anthony Watts et al at surfacestations.org. Dr. Trenberth also states, "I'd expect that all the air conditioners and such churning away would easily be 20 to 40 times greater than the global greenhouse effect." Since the claimed effect of AGW over the past century is a total of 1°F, that would mean that the urban heat island effect would easily be 20° to 40°F compared to 1°F "due to" AGW.  Nonetheless, the piece concludes, "frazzled New Yorkers can expect such heat waves to become more frequent and intense because of climate change warming." Is the hoax again being re-framed from "global warming" to "climate change" to now "climate change warming?"

LiveScience July 30, 2010 [emphasis added]:

The dog days of summer, uh, nights are here. New Yorkers living in Manhattan suffered nighttime temperatures 10 to 15 degrees Fahrenheit higher than in New Jersey or Long Island during the first July heat wave, according to an area-wide network of sensors.

The difference arose because of Manhattan's urban heat island effect, researchers said. Energy demand, air quality, asphalt surfaces and exhaust fumes all prevent the city from cooling off as fast as the surrounding areas. The same holds for other metro areas.

These heat waves could become more frequent in cities, scientists say, mainly as a result of global warming and the increase in high-rises and other buildings.

Muller's latest BEST stuff is the worst so far

Ex climate sceptic' Muller's latest BEST stuff is the worst so far

Non-partisan' group abandons pretence of neutrality

By Andrew Orlowski • Get more from this author

Posted in Energy, 31st July 2012 10:14 GMT  The Register

Analysis Richard Muller's Berkeley Earth Surface Temperature (BEST) project, which began with goodwill from all corners of the climate debate, has made a series of bold announcements (without benefit of peer review) to the effect that global warming is definitely serious and definitely caused by humans. This has aroused derision among formerly supportive climate sceptics, caused an eminent climatologist to abandon the project, and even drawn criticism from generally alarmism-sympathetic media commentators.

Muller, professor of physics at UC Berkeley, is often regarded as a climate sceptic because he has frequently criticised the techniques used by climate scientists in the past and because he accepted funding for BEST from libertarian oil billionaire Charles Koch. When BEST launched in the wake of Climategate, it vowed to be "an independent, non-political, non-partisan group", with Muller promising that "there will be no spin, whatever we find". Critics of the existing temperature establishment, including well known sceptics Anthony Watts and Doug Keenan, welcomed it.

However each announcement has been aggressively trialled in the press not only before the peer review process had judged them ready for publication - which may not be a major issue - but also before anyone outside the BEST project could examine the papers at all. This requires the ordinary reader to take BEST's accompanying press releases on blind faith - which is not a barrier for some journalists, but is far short of acceptable practice. (The publicity is handled by Muller's daughter Elizabeth, who is the actual executive director of BEST. Ms Muller holds degrees in Literature and International Management, and has worked as a consultant in such fields as e-government, "profitable sustainability" and government energy policy. In fact she still does, alongside her work at BEST.)

BEST renewed its science-by-release offensive last week, including an ambitious assertion that Prof Muller could attribute warming to the specific cause of carbon emissions by curve fitting (capturing the trend in the data by assigning a single mathematical function across the entire range).

Now an independent expert who peer-reviewed one of the four new BEST journal submissions has published his comments. The BEST team stated that the paper had not been rejected by peer review and no major flaws had been discovered. This does not appear to be true: the Journal of Geophysical Research ended up rejecting the BEST paper on UHI (Urban Heat Island) effects.

Last September, Ross McKitrick - an associate professor of economics - was asked by the geophysical research journal to review the BEST heat-island paper, which had been submitted to the journal. McKitrick is the economist whose statistical analysis, with Steve McIntyre, of a well-publicised temperature reconstruction led to Congressional hearings in 2006. These hearings endorsed McKitrick and McIntyre's work and raised serious questions about the conduct of the paleoclimate science community.

McKitrick was asked last year to review BEST's approach to grappling with the UHI (Urban Heat Island) effect. It's fair to say he wasn't impressed.

McKitrick said he had discovered "serious shortcomings" in BEST's methods and said "their analysis does not establish valid grounds for the conclusions they assert." He continues: "I suggested the authors be asked to undertake a major revision."

McKitrick's reports are here and here, as short PDFs.

The second comment is worth taking the time to read, as new research using a much more comprehensive classification system puts the lack of rigour in dealing with the UHI effect in the spotlight. BEST appears to replicate the lack of rigour, and worse, appears not to care overmuch:

In their Journal of Geophysical Research submission, the BEST team writes:

"We are not asserting that surface temperature data are unaffected by urbanization, but that a global average based on data that includes stations that may have warmed due to urbanization is not significantly different to one based only on stations that are assumed not to contain urban effects."

McKitrick comments, rather acidly:

I suspect that any reasonable reader, upon completing the paper, would be startled to learn that the authors did not intend to assert that surface temperature data are unaffected by urbanization. I think the above sentence was meant to say something like: “We are not claiming there are no contaminating influences in individual locations, only that they are too small and isolated to affect the global average.” 

Unfortunately the whole issue is whether their methodology reliably supports this conclusion, and in this draft they have done nothing to deal with the evidence that it does not, instead they simply assumed the problems away.

Muller also made the claim that he was a former climate skeptic, which was rapidly disputed.

"If [Al Gore] reaches more people and convinces the world that global warming is real, even if he does it through exaggeration and distortion — which he does, but he’s very effective at it — then let him fly any plane he wants," Muller told climate activist website Grist in October 2008, rather undermining his claim to be sceptical or even impartial at that point.

All this leaves much of the press, including the New York Times - which indulged Muller by giving him an op-ed space last week to announce his latest results - with some explaining to do.

This seems to have been acknowledged even by the New York Times Malthusian-in-Residence, Andy Revkin, a very widely read environment columnist who is generally sympathetic to the warmist position. Revkin wasn't impressed with the Mullers' "PT Barnum showmanship".

Meanwhile, the most distinguished co-author of the early BEST papers last year has declined to be involved in the latest. Dr Judith Curry, Professor and Chair of the School of Earth and Atmospheric Sciences at the Georgia Institute of Technology and President of Climate Forecast Applications Network (CFAN), describes the work as "oversimplistic and not at all convincing in my opinion".

There's a critical analysis by two early participants in BEST, writing in a personal capacity, on Curry's blog, here.

The BEST team uses some interesting techniques, such as kriging – estimating values at locations which haven't been sampled by using a weighted average of neighbouring samples to estimate the 'unknown' value at a given location, so named for geostatistics pioneer Danie Krige – to compensate for sampling biases in station coverage.

The team also examines more stations than existing temperature series. However, BEST fails to use the latest, and more comprehensive, WMO standard for station quality, which results in low quality data. And it's limited, by design, to ignore satellite and sea readings – thus ignoring most of the Earth, which is mostly covered by water.

All in all, it would seem that BEST's stated goal - to produce absolutely undisputable climate data and science, for all that this would mean a regrettable absence of simple, clear soundbites - has been abandoned. 

New paper: Urban Heat Island effect accounts for 56% of warming in urban areas over past 55 years

A paper published last week in the journal Atmospheric Environment finds that the urban heat island effect accounts for 56% of the total temperature increase in South Korean city stations over the past 55 years. Warmists constantly downplay the urban heat island (UHI) effect as insignificant, but as this paper and several others show, the UHI does cause very significant biases with stations reporting higher or rising temperatures because they are poorly sited.

Quantitative Estimates of Warming by Urbanization in South Korea over the Past 55 Years (1954-2008)

Maeng-Ki Kim and Seonae Kim

Abstract: The quantitative values of the urban warming effect over city stations in the Korean peninsula were estimated by using the warming mode of Empirical Orthogonal Function (EOF) analysis of 55 years of temperature data, from 1954 to 2008. The estimated amount of urban warming was verified by applying the multiple linear regression equation with two independent variables: the rate of population growth and the total population.
Through the multiple linear regression equation, we obtained a significance level of 0.05% and a coefficient of determination of 0.60. This means that it is somewhat liable to the estimated effects of urbanization, in spite of the settings of some supposition. The cities that show great warming due to urbanization are Daegu, Pohang, Seoul, and Incheon, which show values of about 1.35, 1.17, 1.16, and 1.10°C, respectively. The areas that showed urban warming less than 0.2°C are Chupungnyeong and Mokpo. On average, the total temperature increase over South Korea was about 1.37 °C; the amount of increase caused by the greenhouse effect is approximately 0.60 °C, and the amount caused by urban warming is approximately 0.77 °C.

Highlights
► The quantitative estimation of the urban warming based on the Empirical Orthogonal Function. ► Urban warming of 0.77 °C for 55 years over South Korea. ► Greenhouse warming of 0.60 °C for 55 years over South Korea. ► Urban warming of about 56% of total temperature increase for 55 years

New paper finds urban heat islands can account for up to 2°C warming

A paper published today in Theoretical and Applied Climatology finds "The impact of urbanization on annual mean surface air temperature has been found to be more than 1 °C in urban areas, and the maximum difference is almost 2 °C." While climate alarmists claim this urban heat island [UHI] effect has had an insignificant effect on observed temperatures, this paper and many others show that the UHI effect is significantly greater than the 0.7C global warming observed since 1850. The majority of weather stations are located near areas of urbanization or have other siting issues that can exaggerate warming. 

Theoretical and Applied Climatology

November 2012

Modeling the climatic effects of urbanization in the Beijing–Tianjin–Hebei metropolitan area

• Mingna Wang, 
• Xuezhen Zhang, 
• Xiaodong Yan

Download PDF (1,176 KB) View Article

Abstract

In this analysis, the weather research and forecasting model coupled with a single-layer urban canopy model is used to simulate the climatic impacts of urbanization in the Beijing–Tianjin–Hebei metropolitan area, which has experienced significant expansion in its urban areas. Two cases examining current landscapes and the sensitivity test of urban areas replaced by cropland have been carried out to explore the changes in the surface air and atmospheric boundary structure. The impact of urbanization on annual mean surface air temperature has been found to be more than 1 °C in urban areas, and the maximum difference is almost 2 °C. The change in near-surface level temperature is most pronounced in winter, but the area influenced by urbanization is slightly larger in summer. The annual mean water vapor mixing ratio and wind speed are both reduced in the urban area. The effect of urbanization can only heat the temperature inside the urban boundary layer, below 850 hPa. The modeling results also indicate that the underlying surface thermal forces induced by the “urban heat island” effect enhance vertical air movement and engenders a convergence zone over urban areas. The convergence at low level together with the moisture increases in the layer between 850 and 700 hPa triggered the increase of convective precipitation.

Why belief in CAGW (Catastrophic Anthropogenic Global Warming) is not currently justified by the standards of the scientific method

A post today at the Paths to Knowledge blog notes that belief in CAGW is not justified under the scientific method because no peer-reviewed study as ever falsified the null hypothesis that global warming is substantially natural. But, the reverse is not true. A recent peer-reviewed study has shown that the null hypothesis [warming is substantially natural] has a statistically significant higher probability of being true than the CAGW hypothesis. Therefore, belief in CAGW is not currently justified by the standards of the scientific method. The IPCC attempts and fails to falsify the null hypothesis using circular reasoning, as noted by Dr. Tim Ball:

Computer models are key to the IPCC circular argument. They’re programmed to the assumptions of the [CAGW] hypothesis, and therefore produce results that confirm the hypothesis. The problem is, nature hasn’t cooperated.

reblogged from Paths to Knowledge:

Posted by strategesis on May 9, 2012

Science does not deal in absolute proofs. The scientific method depends upon falsification of alternative hypotheses until only one remains.

But “falsification” in science is not absolute. Instead, it is a matter of relative probabilities. Such “proof” by falsification of all alternatives is never final: All scientific laws, theories and hypotheses forever remain subject to falsification at any time–at least in principle, even if the odds of that ever happening are infinitesimally small.

All that is required to falsify an hypothesis, or to falsify the currently-accepted theory, is for an alternative hypothesis to be shown–by empirical evidence and quantitative analysis of the relative probabilities–to have a statistically-significant higher probability of being correct.

The CAGW hypothesis is that a) The Earth’s climate is warming, b) The warming is substantially a result of human emissions of CO2 and, c) The magnitude of the warming will be enough to have significant effects, and d) The net effects of the warming will be harmful, and e) The harm caused by the warming will be great enough to be worth the net costs of politically-coerced mitigation.

The alternative hypothesis–which is also the null hypothesis (<= click the link for more info)–is that a) The warming is substantially due to natural causes for which humans are not substantially responsible, and/or b) The magnitude of any human-caused warming will not be not be great enough to have significant effects by itself (regardless of the effects of any warming not caused by man,) and/or c) The net effects of warming will not be harmfull–or if they are, then not by enough to be worth the cost of politically-coerced mitigation.

The null hypothesis has never been falsified. There have been no peer-reviewed studies published that quantitatively analyze both p(CAGW | Historical-Temperature-Data) [the probability that CAGW hypothesis is true, given the historical temperature data] and p(NullHypothesis | Historical-Temperature-Data) [the probability that the Null Hypothesis is true, given the historical temperature data], showing that the former (CAGW) has a statistically significant higher probability of being true than the latter (the null hypothesis–that warming is substantially natural.)Not one.

But the reverse is not true:

HOW NATURAL IS THE RECENT CENTENNIAL WARMING? AN ANALYSIS OF 2249 SURFACE TEMPERATURE RECORDS (Clickable link)

Abstract:

We evaluate to what extent the temperature rise in the past 100 years was a trend or a natural fluctuation and analyze 2249 worldwide monthly temperature records from GISS (NASA) with the 100-year period covering 1906–2005 and the two 50-year periods from 1906 to 1955 and 1956 to 2005. No global records are applied. The data document a strong urban heat island effect (UHI) and a warming with increasing station elevation. For the period 1906–2005, we evaluate a global warming of 0.58°C as the mean for all records. This decreases to 0.41°C if restricted to stations with a population of less than 1000 and below 800 meter above sea level. About a quarter of all the records for the 100-year period show a fall in temperatures. Our hypothesis for the analysis is, as generally in the papers concerned with long-term persistence of temperature records, that the observed temperature records are a combination of long-term correlated records with an additional trend, which is caused for instance by anthropogenic CO2, the UHI or other forcings. We apply the detrended fluctuation analysis (DFA) and evaluate Hurst exponents between 0.6 and 0.65 for the majority of stations, which is in excellent agreement with the literature and use a method only recently published, which is based on DFA, synthetic records and Monte Carlo simulation. As a result, the probabilities that the observed temperature series are natural have values roughly between 40% and 90%, depending on the stations characteristics and the periods considered. “Natural” means that we do not have within a defined confidence interval a definitely positive anthropogenic contribution and, therefore, only a marginal anthropogenic contribution cannot be excluded.


In other words, this study finds that the probability that the observed climate change is some combination of natural variability and urban heat island effect to be as high as 90%. That’s a very strong case in favor of the null hypothesis, and makes it extremely unlikely that there could be a 3-sigma difference in favor of the AGW hypothesis.

Related: Paper: Temperature records show 'predominantly natural fluctuations'

It's Official: 2013 was the 4th7th10th107th... warmest year since the Little Ice Age

Surprisingly, official government temperature records disagree on how much global warming there was in 2013 in comparison other years that are statistically-insignificant-meaningless-hundredths-of-a-degree different. 

One thing is for sure, the globe has fortunately recovered from the Little Ice Age, which coincidentally ended in ~1850 at the start of the instrumental global temperature record, and which shows after UHI-artificial-warming and up-tampered data the temperature rise could have been as much as a whopping 0.7C since 1850. Not only that, the world's oceans have warmed 0.09C over the past 55 years alone!

• NOAA Says 2013 Was The Fourth Warmest Year
• NASA Says 2013 Was Seventh Warmest Year
• RSS AMSU 2013: 10th warmest year on record
• CET: 2013 was 107th warmest year on record [longest instrumental temperature record]
• HADCRU [unofficial analysis]: 2013 8th warmest year on record
• Report: Fed scientists accused of ‘unjustifiably adding on a whopping one degree of phantom warming to the official ‘raw’ temperature record’

Related:

New paper asks: 'Would the 'real' temperature dataset please stand up?'; finds 'We have no ability to know' the true temperature data

A new paper published in Environmental Research Letters examines 8 datasets of temperature & precipitation observations in China over the past 105 years and finds significant unexplained differences between datasets, concluding, 

"Because observations coming from different datasets do have differences, which one we can believe among the various so-called ‘observed climate datasets’? Indeed, we have no ability to know the ‘truth value’"

Indeed, two of the Chinese datasets in the paper show there was essentially no warming in China from 1950-2005.

Furthermore, the paper notes that because we don't know which temperature datasets are correct [if any], climate models based upon flawed temperature data will result in erroneous "tuning" of climate models and therefore biased projections i.e. GIGO]. Excerpt from the conclusion:

All of these results bring about a new challenge in the field of climate change. So-called ‘observed climate datasets’ play important roles in driving hydrologic models, evaluating global circulation models (GCMs) and regional climate models (RCM). Because observations coming from different datasets do have differences, which one we can believe among the various so-called ‘observed climate datasets’? Indeed, we have no ability to know the ‘truth value’; what we need to do is reduce the disagreement among the ‘observed datasets’ and depress their uncertainty.

As lamented in Climategate emails by Phil Jones to James Hansen, if the Chinese stopped their commendable practice of moving thermometers away from contamination by the Urban Heat Island [UHI] effect and instead taken temperature readings contaminated by airport jet exhaust [as the rest of the world did], the Chinese temperature data would have shown more artificial warming.  

One can't deny that temperature data contradictions, contamination, errors and tampering are indeed a worldwide climate phenomenon. 

Related:

Steve Goddard ‏@SteveSGoddardJan 11

Phil Jones calculates 1850 SH temperature to a precision of 0.001, based on a single thermometer in Tasmania pic.twitter.com/HSmNeeIIgr

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New paper finds 100% of the trend in number of "hot days" is artificial, due to poor-siting of thermometers, not global warming

A paper published today in Theoretical and Applied Climatology examines the effect of urbanization on extreme temperature readings in North China and finds statistically significant evidence that urbanization [the Urban Heat Island [UHI] effect] is responsible for 100% of the artificial trend in number of hot days, and 94.1% of the artificial trend in extreme maximum temperatures. In other words, 100% of the reported trends in the number of hot days are due to poor-siting of temperature stations, and have absolutely nothing to do with alleged man-made global warming.

The artificial urbanization contributions to overall trends reported by the authors are:

Urbanization contributions to the overall trends:

hot days 100%

cold days 38%

frost days 42.2%

diurnal temperature range (DTR) 40%

extreme maximum temperature 94.1%

extreme minimum temperature 47%

Urbanization effect on long-term trends of extreme temperature indices at Shijiazhuang station, North China

Latest Results for Theoretical and Applied Climatology 

Based on daily temperature data from an urban station and four rural stations of Shijiazhuang area in Hebei Province, North China, we analyzed the trends of extreme temperature indices series of the urban station (Shijiazhuang station) and rural stations during 1962–2011 and the urbanization effect on the extreme temperature indices of the urban station. The results showed that the trends of annual extreme temperature indices of the urban station and the rural stations are significantly different in the recent 50 years. Urbanization effect on the long-term trends of hot days, cold days, frost days, diurnal temperature range (DTR), extreme maximum temperature, and extreme minimum temperature at the urban station were all statistically significant, reaching 1.10 days/10 years, −2.30 days/10 years, −2.55 days/10 years, −0.20 °C/10 years, 0.16 °C/10 years, and 0.70 °C/10 years, respectively, with the urbanization contributions to the overall trends reaching 100, 38.0, 42.2, 40.0, 94.1, and 47.0 %, respectively. The urbanization effect on trend of ice days was also significant, reaching −0.47 days/10 years. However, no significant urbanization effect on trends of minimum values of maximum temperature and maximum values of minimum temperature had been detected. The urbanization effects in the DTR and extreme minimum temperature series of Shijiazhuang station in wintertime were highly significant.

Good News: New climate models incorporate UHI Bad News: Only focus on CO2

Capturing heat islands in climate models

September 9, 2010 | A team of scientists led by NCAR’s Keith Oleson has incorporated urban areas into a global climate model. The development is important because most models used for predicting future climate change do not account for the urban “heat island” effect. The study will be published in the International Journal of Climatology.

Oleson and colleagues used the Community Climate System Model, an NCAR-based model that uses trillions of calculations to simulate the chemical and physical processes that drive Earth’s climate. After inserting a parameterization for urban surfaces into the CCSM’s land surface component, the researchers ran the model from present day to 2100 under the Intergovernmental Panel on Climate Change (IPCC) A2 emissions scenario, which assumes that global fossil fuel emissions will continue to rise at high levels over the coming century.

Results from the modeling experiment show that present-day annual mean urban air temperatures are up to 4°C warmer than temperatures for surrounding rural areas, a finding that is important for verifying the model’s accuracy since scientists already have observational evidence that urban areas are warmer than surrounding rural areas.

The study found that both urban and rural areas warm substantially by the end of this century as emissions rise, with rural areas warming slightly more than urban—resulting in a decrease in the urban-to-rural contrast. In addition, nighttime urban warming is much greater than daytime urban warming, resulting in a reduced diurnal range in temperature compared to rural areas.

“This study demonstrates that climate models need to begin to account for urban surfaces to more realistically evaluate the impact of climate change on people in the environments where they live,” Oleson says.

He cautions that the study does not account for urban growth or changes in urban form or function; nor does it account for changes in the atmosphere other than increased carbon dioxide concentrations, such as aerosols or other kinds of pollution.
[or account for ocean oscillations, clouds, solar UV activity- which is much more variable than previously thought, negative feedback from water vapor, etc. etc.]

This pair of satellite images provides two views of Atlanta, with the city’s urban core at the center of both images. The top image is a photo-like view of the area, while the bottom image is a land surface temperature map with cooler temperatures in yellow and hotter temperatures in red. Because vegetation cools Earth’s surface through evaporation, the most densely vegetated areas (darkest green in top image) are the coolest areas (palest yellow in bottom image). 

New paper asks: 'Would the 'real' temperature dataset please stand up?'; finds 'We have no ability to know' the true temperature data

A new paper published in Environmental Research Letters examines 8 datasets of temperature & precipitation observations in China over the past 105 years and finds significant unexplained differences between datasets, concluding,

"Because observations coming from different datasets do have differences, which one we can believe among the various so-called ‘observed climate datasets’? Indeed, we have no ability to know the ‘truth value’"

Indeed, two of the Chinese datasets in the paper show there was essentially no warming in China from 1950-2005.

Furthermore, the paper notes that because we don't know which temperature datasets are correct [if any], climate models based upon flawed temperature data will result in erroneous "tuning" of climate models and therefore biased projections i.e. GIGO]. Excerpt from the conclusion:

All of these results bring about a new challenge in the field of climate change. So-called ‘observed climate datasets’ play important roles in driving hydrologic models, evaluating global circulation models (GCMs) and regional climate models (RCM). Because observations coming from different datasets do have differences, which one we can believe among the various so-called ‘observed climate datasets’? Indeed, we have no ability to know the ‘truth value’; what we need to do is reduce the disagreement among the ‘observed datasets’ and depress their uncertainty.

As lamented in Climategate emails by Phil Jones to James Hansen, if the Chinese stopped their commendable practice of moving thermometers away from contamination by the Urban Heat Island [UHI] effect and instead taken temperature readings contaminated by airport jet exhaust [as the rest of the world did], the Chinese temperature data would have shown more artificial warming.  

One can't deny that temperature data contradictions, contamination, errors and tampering are indeed a worldwide climate phenomenon. 

Would the 'real' observed dataset stand up? A critical examination of eight observed gridded climate datasets for China

OPEN ACCESS

Qiaohong Sun, Chiyuan Miao, Qingyun Duan, Dongxian Kong, Aizhong Ye, Zhenhua Di and Wei Gong
PDF (5.39 MB) View article

Abstract

This research compared and evaluated the spatio-temporal similarities and differences of eight widely used gridded datasets. The datasets include daily precipitation over East Asia (EA), the Climate Research Unit (CRU) product, the Global Precipitation Climatology Centre (GPCC) product, the University of Delaware (UDEL) product, Precipitation Reconstruction over Land (PREC/L), the Asian Precipitation Highly Resolved Observational (APHRO) product, the Institute of Atmospheric Physics (IAP) dataset from the Chinese Academy of Sciences, and the National Meteorological Information Center dataset from the China Meteorological Administration (CN05). The meteorological variables focus on surface air temperature (SAT) or precipitation (PR) in China. All datasets presented general agreement on the whole spatio-temporal scale, but some differences appeared for specific periods and regions. On a temporal scale, EA shows the highest amount of PR, while APHRO shows the lowest. CRU and UDEL show higher SAT than IAP or CN05. On a spatial scale, the most significant differences occur in western China for PR and SAT. For PR, the difference between EA and CRU is the largest. When compared with CN05, CRU shows higher SAT in the central and southern Northwest river drainage basin, UDEL exhibits higher SAT over the Southwest river drainage system, and IAP has lower SAT in the Tibetan Plateau. The differences in annual mean PR and SAT primarily come from summer and winter, respectively. Finally, potential factors impacting agreement among gridded climate datasets are discussed, including raw data sources, quality control (QC) schemes, orographic correction, and interpolation techniques. The implications and challenges of these results for climate research are also briefly addressed.

Dr. Nicola Scafetta: "there is little hope that...climate models correctly interpret climate change"

Dr. Nicola Scafetta, author of several peer-reviewed papers explaining the effects of solar activity on Earth's climate, comments on the paper the warmist media is referencing to attempt to dismiss the significance of the Sun on climate. Dr. Scafetta notes that the computer models of this paper and indeed most of climate science are programmed on the basis of false premises, stating, "there is little hope that the traditional climate models correctly interpret climate change and nothing concerning the real climate can be inferred from them because from a false premise everything can be concluded."

nicola scafetta | June 16, 2011 at 9:15 am | Reply   [From Dr. Judith Curry's blog]

Dr. Curry has referenced a work by Feulner G., Rahmstorf S. (2010), that uses a traditional climate model to evaluate the effect of the sun on the climate in the eventuality that a new longer solar minimum would occur. The conclusion is that the Sun would do little in any case.

The problem is whether the traditional climate model is correctly interpreting climate change. The only way to do that is to evaluate whether the climate model properly reconstructs the solar signature observed in the climate.

As I have extensively proven in my papers and by proponents of AGW (see for example Crowley, Science 2000), the traditional climate models produce a signature quite similar to the hockey stick graph by Mann which not only simply disagree with history but has also been seriously put in question under several studies.

Moreover, the traditional climate models also fail to properly reconstruct the correct amplitudes of the climate oscillations that have clear solar/astronomical signature.

Given the above, there is little hope that the traditional climate models correctly interpret climate change and nothing concerning the real climate can be inferred from them because from a false premise everything can be concluded.

In fact, the traditional climate models do not model several mechanisms that may contribute to a significant amplification of the solar impact on climate beginning from a cloud modulation from the cosmic rays which is solar induced.

Because of the lack of the current physics of climate change, the only way to correctly interpret climate is by phenomenological modeling the points to the direct simulation of the temperature patterns as I have proposed.

Once this is done, it is found that solar impact on climate is severely underestimated by the traditional models by a large factor while that the anthropogenic component has been overestimated by at least 2-3 times. That is, while the IPCC claims with the traditional models (which do not reconstruct the climate cycles) that more than 90% of the warming since 1850 is anthropogenic, the reality is very likely that no more than 30% of the warming may be anthropogenic and that this anthropogenic warming may not be GHG [greenhouse gas] induced because may also be UHI [urban heat island] induced, at least in part.

Thus, if the Sun will enter in a new prolonged period of minima, it is very unlikely that the global temperature will go up as predicted by the traditional climate models. It will go down as predicted by the models I have proposed in my papers (look at my web-page). For example “N. Scafetta, “Empirical evidence for a celestial origin of the climate oscillations and its implications”. Journal of Atmospheric and Solar-Terrestrial Physics 72, 951–970 (2010), and “Climate Change and Its Causes, A Discussion About Some Key Issues”

(Also there is a new paper under press on these issues)