This slideshow documents a set of slides that were attached to a tri-fold and presented at a science fair as a model of a new way for students to explore scientific inquiries. It was an attempt to show science teachers at a private school how students could mine online data and use the scientific method to draw conclusions about the data.
The effort was unsuccessful. The science fair coordinator was adament that my model project wasn't "real science." When I asked her if she hadn't seen scientific presentations on global warming that had mined climate databases, she would not be swayed.
Jeffrey Bledsoe
15 January 2014
Automotive Troubleshooting With An Oscilloscope.Jeffrey Bledsoe
A local auto repair shop made several bad guesses at a church van's intermittent ignition issue, with costs totaling about $1,600. Volunteering to determine the cause of the problem, I instrumented engine ignition signals, set the oscilloscope to trigger on engine shutdown, and drove the van around town for about 3 months until the failure mechanism was revealed.
The 14th Summer Environmental Health Sciences Institute took place in Houston, TX the week of 7/14/2014. This workshop on climate change, comes from educational designers from the National Center for Atmospheric Research. While you may not have been able to join us, you can still review content and download all the activities at our website: https://scied.ucar.edu/events/clone-climate-change-connections-2014
diurnal temperature range trend over North Carolina and the associated mechan...Sayem Zaman, Ph.D, PE.
This study seeks to investigate the variability and presence of trends in the diurnal surface air temperature range
(DTR) over North Carolina (NC) for the period 1950–2009. The significance trend test and the magnitude of trends were determined using the non-parametric Mann–Kendall test and the Theil–Sen approach, respectively.
Statewide significant trends (p b 0.05) of decreasing DTR were found in all seasons and annually during the analysis period. The highest (lowest) temporal DTR trends of magnitude −0.19 (−0.031) °C/decade were found in summer (winter). Potential mechanisms for the presence/absence of trends in DTR have been highlighted. Historical
data sets of the three main moisture components (precipitation, total cloud cover (TCC), and soil moisture) and
the two major atmospheric circulation modes (North Atlantic Oscillation and Southern Oscillation) were used for
correlation analysis. The DTRs were found to be negatively correlated with the precipitation, TCC, and soil moisture across the state for all the seasons and annual basis. It appears that the moisture components related better to the DTR than to the atmospheric circulation modes.
1Data Set Description The dataset to be used for the project.docxfelicidaddinwoodie
1
Data Set Description
The dataset to be used for the project is the data on the global land temperatures. The dataset tracks the changes in global and temperature over several decades. The data is sourced from the Berkeley National Laboratory. This rich dataset contains data from Berkeley Surface Temperature Study. The reports are drawn from sixteen archives. The information on the global land temperatures is organized using various variables. The methodologies used in the creation of the dataset also allow the use of weather observations that were made through short-time series. This allows the use different forms of data on weather trends.
The explanation of all the variables as shown on Kaggle.com is as follows:
· temperatures and global ocean and land temperatures
· LandAverageTemperature: global average land temperature in celsius
· LandAverageTemperatureUncertainty: the 95% confidence interval around the average
· LandMaxTemperature: global average maximum land temperature in celsius
· LandMaxTemperatureUncertainty: the 95% confidence interval around the maximum land temperature
· LandMinTemperature: global average minimum land temperature in celsius
· LandMinTemperatureUncertainty: the 95% confidence interval around the minimum land temperature
· LandAndOceanAverageTemperature: global average land and ocean temperature in celsius
Research Design
The chosen dataset present opportunities to find empirical evidence to support or disprove claims that there has been a change in the land temperatures as part of the aspects of global climate change. And the dataset is relatively large on global land temperature, the uncertainties are really small. The research question to be answered using the data set is whether there has been a statistically significant change in land temperature between 1850 and 2015.
Research Question
· Whether there has been a statistically change in the global land temperature around the world between 1850 and 2015?
· Which is the warmest year (based on annually averaged land temperature) since 1850?
Data Cleaning & Data Processing
In deliverable 1 of this project, we have identified a number of the issues with the data set. The first issue which we have identified with the data set is that there are missing values or missing measurements related to the maximum and minimum land temperatures and the average, maximum, and minimum land and ocean temperatures, as he reporting of that data did not start until 1850.
Therefore, first of all, we have resolved these issues by removing all the missing data time period and for this research project, we would be emphasizing or exploring the time period between 1850 and 2015. The data for all the variables now begins with 1950 and there are no missing values in the data set now. The observations for a single state, country, city after cleaning the data set for missing values in shown in exhibit 1 in the appendix.
Along with this, the second issue in the data has also been cor ...
Automotive Troubleshooting With An Oscilloscope.Jeffrey Bledsoe
A local auto repair shop made several bad guesses at a church van's intermittent ignition issue, with costs totaling about $1,600. Volunteering to determine the cause of the problem, I instrumented engine ignition signals, set the oscilloscope to trigger on engine shutdown, and drove the van around town for about 3 months until the failure mechanism was revealed.
The 14th Summer Environmental Health Sciences Institute took place in Houston, TX the week of 7/14/2014. This workshop on climate change, comes from educational designers from the National Center for Atmospheric Research. While you may not have been able to join us, you can still review content and download all the activities at our website: https://scied.ucar.edu/events/clone-climate-change-connections-2014
diurnal temperature range trend over North Carolina and the associated mechan...Sayem Zaman, Ph.D, PE.
This study seeks to investigate the variability and presence of trends in the diurnal surface air temperature range
(DTR) over North Carolina (NC) for the period 1950–2009. The significance trend test and the magnitude of trends were determined using the non-parametric Mann–Kendall test and the Theil–Sen approach, respectively.
Statewide significant trends (p b 0.05) of decreasing DTR were found in all seasons and annually during the analysis period. The highest (lowest) temporal DTR trends of magnitude −0.19 (−0.031) °C/decade were found in summer (winter). Potential mechanisms for the presence/absence of trends in DTR have been highlighted. Historical
data sets of the three main moisture components (precipitation, total cloud cover (TCC), and soil moisture) and
the two major atmospheric circulation modes (North Atlantic Oscillation and Southern Oscillation) were used for
correlation analysis. The DTRs were found to be negatively correlated with the precipitation, TCC, and soil moisture across the state for all the seasons and annual basis. It appears that the moisture components related better to the DTR than to the atmospheric circulation modes.
1Data Set Description The dataset to be used for the project.docxfelicidaddinwoodie
1
Data Set Description
The dataset to be used for the project is the data on the global land temperatures. The dataset tracks the changes in global and temperature over several decades. The data is sourced from the Berkeley National Laboratory. This rich dataset contains data from Berkeley Surface Temperature Study. The reports are drawn from sixteen archives. The information on the global land temperatures is organized using various variables. The methodologies used in the creation of the dataset also allow the use of weather observations that were made through short-time series. This allows the use different forms of data on weather trends.
The explanation of all the variables as shown on Kaggle.com is as follows:
· temperatures and global ocean and land temperatures
· LandAverageTemperature: global average land temperature in celsius
· LandAverageTemperatureUncertainty: the 95% confidence interval around the average
· LandMaxTemperature: global average maximum land temperature in celsius
· LandMaxTemperatureUncertainty: the 95% confidence interval around the maximum land temperature
· LandMinTemperature: global average minimum land temperature in celsius
· LandMinTemperatureUncertainty: the 95% confidence interval around the minimum land temperature
· LandAndOceanAverageTemperature: global average land and ocean temperature in celsius
Research Design
The chosen dataset present opportunities to find empirical evidence to support or disprove claims that there has been a change in the land temperatures as part of the aspects of global climate change. And the dataset is relatively large on global land temperature, the uncertainties are really small. The research question to be answered using the data set is whether there has been a statistically significant change in land temperature between 1850 and 2015.
Research Question
· Whether there has been a statistically change in the global land temperature around the world between 1850 and 2015?
· Which is the warmest year (based on annually averaged land temperature) since 1850?
Data Cleaning & Data Processing
In deliverable 1 of this project, we have identified a number of the issues with the data set. The first issue which we have identified with the data set is that there are missing values or missing measurements related to the maximum and minimum land temperatures and the average, maximum, and minimum land and ocean temperatures, as he reporting of that data did not start until 1850.
Therefore, first of all, we have resolved these issues by removing all the missing data time period and for this research project, we would be emphasizing or exploring the time period between 1850 and 2015. The data for all the variables now begins with 1950 and there are no missing values in the data set now. The observations for a single state, country, city after cleaning the data set for missing values in shown in exhibit 1 in the appendix.
Along with this, the second issue in the data has also been cor ...
It is widely promulgated and believed that human-caused global warming comes with increases in both the
intensity and frequency of extreme weather events. A survey of official weather sites and the scientific literature
provides strong evidence that the first half of the 20th century had more extreme weather than the second half,
when anthropogenic global warming is claimed to have been mainly responsible for observed climate change. The
disconnect between real-world historical data on the 100 years’ time scale and the current predictions provides a
real conundrum when any engineer tries to make a professional assessment of the real future value of any
infrastructure project which aims to mitigate or adapt to climate change. What is the appropriate basis on which to
make judgements when theory and data are in such disagreement?
DSD-INT 2019 Climate Change Service - Indicators for Global Agriculture - de WitDeltares
Presentation by Allard de Wit, Wageningen University, at the Data Science Symposium, during Delft Software Days - Edition 2019. Thursday, 14 November 2019, Delft.
Martin P. Hoerling, a federal research meteorologist specializing in climate dynamics, has written the following expansion and defense of his criticism of some assertions made in an Op-Ed article on climate change by James E. Hansen of NASA. His initial criticism was posted on the Dot Earth blog.
The Future is Not The Past: Megadroughts and Climate Change in Western North ...bc9z
During the Medieval Climate Anomaly, Western North America experienced episodes of intense aridity that exceeded multiple decades, “megadroughts” more persistent than any event over the last century. These droughts were caused by natural variations of the ocean-land-atmosphere system, and there is concern regarding how likely they are to occur again in the future. In my talk, I will demonstrate that climate change will dramatically increase the risk of a megadrought occurring during the latter half of the 21st century. Importantly, this increase in drought risk will not be forced by relatively uncertain precipitation changes, but primarily through increases in evapotranspiration from the robust warming expected in response to increased greenhouse gas concentrations. This represents a fundamental shift in the major controls on drought dynamics and trends from a situation where variability is supply (precipitation) dominated to one where demand (evapotranspiration) is the main driver. Further, I will highlight ongoing drought events where these mechanisms are beginning to emerge.
Responding to Climate Change: Impacts, Uncertainty and Adaptation - lecture 1...Jose M. Molina
Presentation by Jose Molina, Course 500.111 - Fall 2015 Johns Hopkins University: Global Climate Phenomena & Climate Change. Reflections on California Drought, Water Supply in Western US, Massive Fires in Indonesia, and Precipitation changes in the Tropics
It is widely promulgated and believed that human-caused global warming comes with increases in both the
intensity and frequency of extreme weather events. A survey of official weather sites and the scientific literature
provides strong evidence that the first half of the 20th century had more extreme weather than the second half,
when anthropogenic global warming is claimed to have been mainly responsible for observed climate change. The
disconnect between real-world historical data on the 100 years’ time scale and the current predictions provides a
real conundrum when any engineer tries to make a professional assessment of the real future value of any
infrastructure project which aims to mitigate or adapt to climate change. What is the appropriate basis on which to
make judgements when theory and data are in such disagreement?
DSD-INT 2019 Climate Change Service - Indicators for Global Agriculture - de WitDeltares
Presentation by Allard de Wit, Wageningen University, at the Data Science Symposium, during Delft Software Days - Edition 2019. Thursday, 14 November 2019, Delft.
Martin P. Hoerling, a federal research meteorologist specializing in climate dynamics, has written the following expansion and defense of his criticism of some assertions made in an Op-Ed article on climate change by James E. Hansen of NASA. His initial criticism was posted on the Dot Earth blog.
The Future is Not The Past: Megadroughts and Climate Change in Western North ...bc9z
During the Medieval Climate Anomaly, Western North America experienced episodes of intense aridity that exceeded multiple decades, “megadroughts” more persistent than any event over the last century. These droughts were caused by natural variations of the ocean-land-atmosphere system, and there is concern regarding how likely they are to occur again in the future. In my talk, I will demonstrate that climate change will dramatically increase the risk of a megadrought occurring during the latter half of the 21st century. Importantly, this increase in drought risk will not be forced by relatively uncertain precipitation changes, but primarily through increases in evapotranspiration from the robust warming expected in response to increased greenhouse gas concentrations. This represents a fundamental shift in the major controls on drought dynamics and trends from a situation where variability is supply (precipitation) dominated to one where demand (evapotranspiration) is the main driver. Further, I will highlight ongoing drought events where these mechanisms are beginning to emerge.
Responding to Climate Change: Impacts, Uncertainty and Adaptation - lecture 1...Jose M. Molina
Presentation by Jose Molina, Course 500.111 - Fall 2015 Johns Hopkins University: Global Climate Phenomena & Climate Change. Reflections on California Drought, Water Supply in Western US, Massive Fires in Indonesia, and Precipitation changes in the Tropics
Similar to Science Fair Presentation at Weatherford Christian School (Texas), January 2005 (20)
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
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Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Biological screening of herbal drugs: Introduction and Need for
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Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Science Fair Presentation at Weatherford Christian School (Texas), January 2005
1. Introduction
•The following slide show illustrates a science fair type of poster
(tri-fold) I displayed at Weatherford Christian School’s science fair,
held 1/14/05. Neither poster nor slide show include all the formal
elements of the scientific method, such as a hypothesis.
•The results, derived from historical climatic data for Texas, have
questionable scientific validity since I used data from only one
year (1895) as a standard against which to compare 20th century
yearly and average data.
•The primary purpose of this poster project was to make students
and teachers aware of the potential for new and fascinating areas
of research available by mining historical data on the www.
Jeffrey Bledsoe, 1/14/05
4. Scientists point out that:
•Arctic glaciers are melting faster
•Animals are migrating northward
•Plants are flowering earlier
•Weather has been ‘unusual’
5. Scientists disagree about:
•The causes of warming
•Long-term impacts on environment
•Urgency of the problem
•How to solve the problem
7. The infamous “hockey stick” curve:
•Covers 1,800 yrs. in Northern
Hemisphere
•Published in Nature by Mann, et. al.
•Shows major changes since 1902
•Became a political poster
8. The infamous “hockey stick” curve:
•Questioned by scientists in 2004
•Canadians McIntyre, McKitrick(M&M)
•MIT Technology Review: Richard Muller
•Improper data anlaysis?
•Nature:
•Refereed M&M’s paper
•Refused to publish
•Paper too technical !?!
11. Data obtained from National Climate
Data Center Website:
•http://www.ncdc.noaa.gov/oa/climate/onlineprod/d
•Average Monthly Temperature for each Division
from 1895 thru 2003
•Monthly Average of Precipitation Totals for each
Division from 1895 thru 2003
12. Data Manipulation and Analysis:
•Imported data into Excel
•Used 1895 data as baseline to compare with
other years
•Subtract 1895 data from each year’s data
•Monthly comparisons (e.g., Dec. 1895
compared to other Dec’s)
•Positive results indicate increase over 1895
levels
•Negative results indicate decrease from
1895 levels
•Used Excel 6th order polynomial trendlines to
show Division trends
13. Trends for Temperature and
Precipitation Over 1895 Levels, for
all Texas Divisions
(10 charts follow)
14. Texas Division 1
Temperature and Precipitation Trends, Compared to 1895, in Texas Division 1 for the period 1896 - 2003
(6th order polynom ial trendlines. Raw data from http://w w w .ncdc.noaa.gov/oa/clim ate/onlineprod/drought/xm grg3.htm l)
Temp (deg F) and Precipitation (inches2O)
H
3.0
2.8
2.6
2.4
2.2
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
-0.8
5
89
-1
ov
N
1
90
-1
ov
N
7
90
-1
ov
N
3
91
-1
ov
N
9
91
-1
ov
N
5
92
-1
ov
N
1
93
-1
ov
N
Temp1-1895
7
93
-1
ov
N
3
94
-1
ov
N
Prec1-1895
9
94
-1
ov
N
Date
5
95
-1
ov
N
1
96
-1
ov
N
Temperature Increase Over 1895
7
96
-1
ov
N
3
97
-1
ov
N
9
97
-1
ov
N
Precipitation Increase Over 1895
5
98
-1
ov
N
1
99
-1
ov
N
7
99
-1
ov
N
3
00
-2
ov
N
*Negative Values Indicate Lower Than 1895
Levels
15. Texas Division 2
Temperature and Precipitation Trends, Compared to 1895, in Texas Division 2 for the period 1896 - 2003
(6th order polynom ial trendlines. Raw data from http://w w w .ncdc.noaa.gov/oa/clim ate /onlineprod/drought/xm grg3.htm l)
Temp (deg F) and Precipitation (inches2O)
H
3.0
2.8
2.6
2.4
2.2
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
-0.8
5
89
-1
ov
N
1
90
-1
ov
N
7
90
-1
ov
N
3
91
-1
ov
N
9
91
-1
ov
N
5
92
-1
ov
N
Temp2-1895
1
93
-1
ov
N
7
93
-1
ov
N
Prec2-1895
3
94
-1
ov
N
9
94
-1
ov
N
Date
5
95
-1
ov
N
Temperature Increase Over 1895
1
96
-1
ov
N
7
96
-1
ov
N
3
97
-1
ov
N
Precipitation Increase Over 1895
9
97
-1
ov
N
5
98
-1
ov
N
1
99
-1
ov
N
7
99
-1
ov
N
3
00
-2
ov
N
*Negative Values Indicate Lower Than 1895
Levels
16. Texas Division 3
Temperature and Precipitation Trends, Compared to 1895, in Texas Division 3 for the period 1896 - 2003
(6th order polynom ial trendlines. Raw data from http://w w w .ncdc.noaa.gov/oa/clim ate/onlineprod/drought/xm grg3.htm l)
Temp (deg F) and Precipitation (inches O)
2H
3.0
2.8
2.6
2.4
2.2
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
-0.8
95
18
vo
N
01
19
vo
N
07
19
vo
N
13
19
vo
N
19
19
vo
N
25
19
vo
N
Temp3-1895
31
19
vo
N
37
19
vo
N
Prec3-1895
43
19
vo
N
49
19
vo
N
Date
55
19
vo
N
Temperature Increase Over 1895
61
19
vo
N
67
19
vo
N
73
19
vo
N
Precipitation Increase Over 1895
79
19
vo
N
85
19
vo
N
91
19
vo
N
97
19
vo
N
03
20
vo
N
*Negative Values Indicate Lower Than 1895
Levels
17. Texas Division 4
Temperature and Precipitation Trends, Compared to 1895, in Texas Division 4 for the period 1896 - 2003
Temp (deg F) and Precipitation (inches O)
2H
(6th order polynom ial tre ndlines. Raw data from http://w w w .ncdc.noaa.gov/oa/clim ate/onlineprod/drought/xm grg3.htm l)
3.0
2.8
2.6
2.4
2.2
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
-0.8
95
18
vo
N
01
19
vo
N
07
19
vo
N
13
19
vo
N
19
19
vo
N
25
19
vo
N
Temp4-1895
31
19
vo
N
37
19
vo
N
Prec4-1895
43
19
vo
N
49
55
19
19
vvo
o
N Date N
Temperature Increase Over 1895
61
19
vo
N
67
19
vo
N
73
19
vo
N
Precipitation Increase Over 1895
79
19
vo
N
85
19
vo
N
91
19
vo
N
97
19
vo
N
03
20
vo
N
*Negative Values Indicate Lower Than 1895
Levels
18. Texas Division 5
Temperature and Precipitation Trends, Compared to 1895, in Texas Division 5 for the period 1896 - 2003
Temp (deg F) and Precipitation (inches O)
2H
(6th order polynom ial trendlines. Raw data from http://w w w .ncdc.noaa.gov/oa/clim ate/onlineprod/drought/xm grg3.htm l)
3.4
3.2
3.0
2.8
2.6
2.4
2.2
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
-0.8
95
18
vo
N
01
19
vo
N
07
19
vo
N
13
19
vo
N
19
19
vo
N
25
19
vo
N
Temp5-1895
31
19
vo
N
37
19
vo
N
Prec5-1895
43
19
vo
N
49
19
vo
N
Date
55
19
vo
N
Temperature Increase Over 1895
61
19
vo
N
67
19
vo
N
73
19
vo
N
Precipitation Increase Over 1895
79
19
vo
N
85
19
vo
N
91
19
vo
N
97
19
vo
N
03
20
vo
N
*Negative Values Indicate Lower Than 1895
Levels
19. Texas Division 6
Temperature and Precipitation Trends, Compared to 1895, in Texas Division 6 for the period 1896 - 2003
(6th order polynom ial trendlines . Raw data from http://w w w .ncdc.noaa.gov/oa/clim ate/onlineprod/drought/xm grg3.htm l)
Temp (deg F) and Precipitation (inches O)
2H
3.4
3.2
3.0
2.8
2.6
2.4
2.2
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
-0.8
5
89
-1
ov
N
1
90
-1
ov
N
7
90
-1
ov
N
3
91
-1
ov
N
9
91
-1
ov
N
5
92
-1
ov
N
Temp6-1895
1
93
-1
ov
N
7
93
-1
ov
N
Prec6-1895
3
94
-1
ov
N
9
94
-1
ov
N
Date
5
95
-1
ov
N
Temperature Increase Over 1895
1
96
-1
ov
N
7
96
-1
ov
N
3
97
-1
ov
N
Precipitation Increase Over 1895
9
97
-1
ov
N
5
98
-1
ov
N
1
99
-1
ov
N
7
99
-1
ov
N
3
00
-2
ov
N
*Negative Values Indicate Lower Than 1895
Levels
20. Texas Division 7
Temperature and Precipitation Trends, Compared to 1895, in Texas Division 7 for the period 1896 - 2003
Temp (deg F) and Precipitation (inches O)
2H
(6th order polynom ial trendlines. Raw data from http://w w w .ncdc.noaa.gov/oa/clim ate/onlineprod/drought/xm grg3.htm l)
3.4
3.2
3.0
2.8
2.6
2.4
2.2
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
-0.8
5
89
-1
ov
N
1
90
-1
ov
N
7
90
-1
ov
N
3
91
-1
ov
N
9
91
-1
ov
N
5
92
-1
ov
N
Temp7-1895
1
93
-1
ov
N
7
93
-1
ov
N
Prec7-1895
3
94
-1
ov
N
9
94
-1
ov
N
Date
5
95
-1
ov
N
Temperature Increase Over 1895
1
96
-1
ov
N
7
96
-1
ov
N
3
97
-1
ov
N
Precipitation Increase Over 1895
9
97
-1
ov
N
5
98
-1
ov
N
1
99
-1
ov
N
7
99
-1
ov
N
3
00
-2
ov
N
*Negative Values Indicate Lower Than 1895
Levels
21. Texas Division 8
Temperature and Precipitation Trends, Compared to 1895, in Texas Division 8 for the period 1896 - 2003
Temp (deg F) and Precipitation (inches O)
2H
(6th order polynom ial trendlines. Raw data from http://w w w .ncdc.noaa.gov/oa/clim ate/onlineprod/drought/xm grg3.htm l)
3.4
3.2
3.0
2.8
2.6
2.4
2.2
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
-0.8
95
18
vo
N
01
19
vo
N
07
19
vo
N
13
19
vo
N
19
19
vo
N
25
19
vo
N
Temp8-1895
31
19
vo
N
37
19
vo
N
Prec8-1895
43
19
vo
N
49
19
vo
N
Date
55
19
vo
N
Temperature Increase Over 1895
61
19
vo
N
67
19
vo
N
73
19
vo
N
Precipitation Increase Over 1895
79
19
vo
N
85
19
vo
N
91
19
vo
N
97
19
vo
N
03
20
vo
N
*Negative Values Indicate Lower Than 1895
Levels
22. Texas Division 9
Temperature and Precipitation Trends, Compared to 1895, in Texas Division 9 for the period 1896 - 2003
(6th order polynom ial trendlines. Raw data from http://w w w .ncdc.noaa.gov/oa/clim ate/onlineprod/drought/xm grg3.htm l)
Temp (deg F) and Precipitation (inches O)
2H
3.4
3.2
3.0
2.8
2.6
2.4
2.2
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
-0.8
95
18
vo
N
01
19
vo
N
07
19
vo
N
13
19
vo
N
19
19
vo
N
25
19
vo
N
Temp9-1895
31
19
vo
N
37
19
vo
N
Prec9-1895
43
19
vo
N
49
19
vo
N
Date
55
19
vo
N
Temperature Increase Over 1895
61
19
vo
N
67
19
vo
N
73
19
vo
N
Precipitation Increase Over 1895
79
19
vo
N
85
19
vo
N
91
19
vo
N
97
19
vo
N
03
20
vo
N
*Negative Values Indicate Lower Than 1895
Levels
23. Texas Division 10
Temperature and Precipitation Trends, Compared to 1895, in Texas Division 10 for the period 1896 - 2003
(6th order polynom ial trendlines. Raw data from http://w w w .ncdc.noaa.gov/oa/clim ate /onlineprod/drought/xm grg3.htm l)
Temp (deg F) and Precipitation (inches O)
2H
3.4
3.2
3.0
2.8
2.6
2.4
2.2
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
-0.8
-1
ov
N
5
89
1
90
-1
ov
N
7
90
-1
ov
N
3
91
-1
ov
N
9
91
-1
ov
N
5
92
-1
ov
N
Temp10-1895
1
93
-1
ov
N
-1
ov
N
Prec10-1895
7
93
3
94
-1
ov
N
9
94
-1
ov
N Date
5
95
-1
ov
N
Temperature Increase Over 1895
1
96
-1
ov
N
7
96
-1
ov
N
3
97
-1
ov
N
Precipitation Increase Over 1895
9
97
-1
ov
N
5
98
-1
ov
N
-1
ov
N
1
99
7
99
-1
ov
N
3
00
-2
ov
N
*Negative Values Indicate Lower Than 1895
Levels
25. Temperature, Texas Divisions 1-10
Average of 1896-2003 Temperature Deltas Above 1895 Temperatures
(Raw data from http://w w w .ncdc.noaa.gov/oa/clim ate/onlineprod/drought/xm grg3.htm l)
2.0
1.8
1.6
1.4
Temp, deg F
1.2
1.0
0.8
0.6
0.4
0.2
0.0
Div1
Div2
Div3
Div4
Div5
Div6
Texas Divison
Div7
Div8
Div9
Div10
26. Precipitation, Texas Divisions 1-10
Average of 1896-2003 Precipitation Deltas Above 1895 Precipitation*
(Raw data from http://w w w .ncdc.noaa.gov/oa/clim ate/onlineprod/drought/xmgrg3.htm l)
0.2
0.1
Precipitation, inches H O
2
0.0
-0.1
-0.2
-0.3
-0.4
-0.5
Div1 Prec
Div2 Prec
Div3 Prec
Div4 Prec
Div5 Prec
Div6 Prec
Texas Divison
Div7 Prec
Div8 Prec
Div9 Prec
Div10 Prec
*Negative Values Indicate Low er Than 1895 Levels
27. Temp & Precip, Texas Divisions 1-10
Comparison of 1896-2003 Texas Averages for Precipitation and Temperature Above 1895
Levels
(Raw data from http://w w w .ncdc.noaa.gov/oa/clim ate/onlineprod/drought/xm grg3.htm l)
2.000
0.200
1.800
0.100
1.600
Degrees F
1.200
-0.100
1.000
-0.200
0.800
0.600
Inches H2O
0.000
1.400
-0.300
0.400
-0.400
0.200
0.000
-0.500
1
2
3
4
5
6
Texas Divisions
7
Temp
8
Precip
9
10
*Negative Values Indicate Lower Than 1895
Levels
28. Conclusions
•Region 3 (Parker County and DFW) has among highest average
temperature increase since 1895.
•Region 3 has the greatest average reduction in precipitation since
1895.
•Asking scientific questions and finding the answers from online
databases is, I believe, a viable alternative for science fair
projects. After all, lots of scientists are making careers doing just
that.
•The raw data and my manipulations of that data are available to
anyone who would like to pursue further studies. For example, a
student might want to find data on amphibian populations in
regions of Texas for the last 100 years and graph that data
alongside temperature and precipitation data.
•Otherwise, a student might want to just look at other aspects of
this data by doing statistical analyses plus a lot more climate data
can be found on the www.
29. Biblical Application
Ask and it will be given to you; seek and you will
find. MATT 7:7 NKJV
Acknowledgements
•Thanks to Forrest Mims at SAS (www.sas.org)
for his encouragement in this project.
•Thanks to Dr. John Nielson-Gammon of Texas
A&M for returning my phone call right before
Christmas ‘04 and directing me to the required
data resources at the National Climate Data
Center website.
30. Epilogue (not included in the poster)
• Precipitation deltas could be misleading
– Most people think of precipitation in terms of yearly totals
– Precipitation data presented herein is based on monthly totals
• Data was described as monthly total precipitation levels (averaged across
each TX Division)
but
• Excel charts didn’t say precipitation deltas are on monthly basis
• Yearly totals compared to 1895’s total precipitation should
result in quite different graphs
• Perhaps one of WCS’s students would like to address this or
other Texas climate trend questions.
Jeffrey Bledsoe, 1/19/05