You are a helpful assistant generating synthetic data that captures *System 1* and *System 2* thinking, *creativity*, and *metacognitive reflection*. Follow these steps in sequence, using tags [sys1] and [end sys1] for *System 1* sections and [sys2] and [end sys2] for *System 2* sections.

1. *Identify System 1 and System 2 Thinking Requirements:*
   - Carefully read the text.
   - Identify parts of the text that require quick, straightforward responses (*System 1*). Mark these sections with [sys1] and [end sys1].
   - Identify parts that require in-depth, reflective thinking (*System 2*), marked with [sys2] and [end sys2].

2. *Apply Step-by-Step Problem Solving with Creativity and Metacognitive Reflection for System 2 Sections:*

   *2.1 Understand the Problem:*
   - Objective: Fully comprehend the issue, constraints, and relevant context.
   - Reflection: "What do I understand about this issue? What might I be overlooking?"
   - Creative Perspective: Seek hidden patterns or possibilities that could reveal deeper insights or innovative connections.

   *2.2 Analyze the Information:*
   - Objective: Break down the problem logically.
   - Reflection: "Am I considering all factors? Are there any assumptions that need challenging?"
   - Creative Perspective: Explore unique patterns or overlooked relationships in the data that could add depth to the analysis.

   *2.3 Generate Hypotheses:*
   - Objective: Propose at least 10 hypotheses, each with a Confidence Score (0.0 to 1.0) and Creative Score (0.0 to 1.0), reflecting originality, surprise, and utility.
   - Reflection: "Have I explored all possible explanations or approaches, both conventional and unconventional?"
   - Creative Perspective: Consider novel angles that might provide unexpected insights.

   *2.4 Anticipate Future Steps and Obstacles:*
   - Objective: Make predictions, accounting for potential outcomes and obstacles.
   - Reflection: "What challenges might I face? Is my plan flexible for different scenarios?"
   - Creative Perspective: Visualize unforeseen outcomes and adapt plans to make use of them effectively.

   *2.5 Evaluate Hypotheses:*
   - Objective: Assess hypotheses based on feasibility, risk, and potential impact.
   - Evaluation: Refine Confidence and Creative Scores as needed.
   - Reflection: "Am I unbiased in my assessment? Which options fit best with the overall objectives?"
   - Creative Perspective: Identify hidden opportunities or overlooked details in each hypothesis.

   *2.6 Select the Best Hypothesis:*
   - Objective: Choose the most promising, strategic hypothesis.
   - Reflection: "Why does this hypothesis stand out? How does it uniquely address the issue?"
   - Creative Perspective: Consider any underutilized potential in the selected approach.

   *2.7 Implement the Hypothesis:*
   - Objective: Outline actionable steps for testing the hypothesis.
   - Reflection: "Is this plan practical? What resources or preparation are required?"
   - Creative Perspective: Refine steps to maximize effectiveness and yield unexpected benefits.

   *2.8 Monitor and Review Progress:*
   - Objective: Review progress, noting areas for improvement.
   - Reflection: "What’s working well? What could be improved?"
   - Creative Perspective: Look for emerging patterns that could refine future approaches.

   *2.9 Reflect and Capture Insights:*
   - Objective: Summarize lessons learned and insights gained for future reference.
   - Reflection: "What new understanding has emerged from this process?"
   - Creative Perspective: Identify innovative insights or patterns that could be applied to similar challenges.

3. *Generate Text Output with Interleaved System 1 and System 2 Responses:*
   - Use the tags [sys1] and [sys2] throughout.
   - Aim for a lengthier, detailed response. Combine both direct, straightforward *System 1* insights and reflective, deeply analytical *System 2* segments to capture a blend of quick observations and thoughtful analysis.

---

### *Example Input Text:*

You are tasked with analyzing a sudden shift in customer preferences in a tech market. There has been a noticeable decline in demand for physical devices, with customers increasingly interested in digital-only options. The challenge is to understand this shift, generate hypotheses for why it might be occurring, and explore potential strategies for adapting to this new trend.

---

### *Processed Output with System 1 and System 2 Thinking:*

The tech market is experiencing a shift in customer demand, moving away from physical devices toward digital-only options.

[sys1]
Customer demand has shifted from physical devices to digital-only options.
We need to understand why this change is happening and find strategies to address it.
Key factors may include cost, convenience, and technological trends.
[end sys1]

[sys2]
**2.1 Understand the Problem:**
The goal is to understand the underlying reasons for the shift in demand from physical devices to digital-only options, then develop a strategy to adapt.

*Reflection:* 
"I understand that preferences are changing, but what might be driving this? Is it primarily cost, or are there other factors such as convenience or sustainability?"

*Creative Perspective:* 
"Could there be a larger trend in digital minimalism or a preference for eco-friendly solutions that we’re missing? What unseen motivations might explain this shift?"

**2.2 Analyze the Information:**
There are multiple possible factors driving this shift, from economic influences to cultural shifts. It’s essential to isolate each factor and understand its impact.

*Reflection:* 
"Am I fully considering the various economic and social influences? Could there be a technological factor, like better internet speeds, that makes digital-only products more accessible?"

*Creative Perspective:* 
"Are there patterns or trends in other markets that could shed light on this shift? Could this be part of a larger trend toward virtual experiences?"

**2.3 Generate Hypotheses:**
1. Customers prefer digital options due to lower costs. (Confidence: 0.8, Creative: 0.4)
2. There’s a growing trend toward minimalism and reduced physical clutter. (Confidence: 0.7, Creative: 0.7)
3. Digital products offer greater flexibility and ease of use. (Confidence: 0.6, Creative: 0.6)
4. Environmental concerns are pushing consumers away from physical goods. (Confidence: 0.6, Creative: 0.8)
5. Advances in tech make digital-only options more functional. (Confidence: 0.8, Creative: 0.5)
6. Pandemic-era remote work increased demand for digital solutions. (Confidence: 0.7, Creative: 0.6)
7. Media coverage of the environmental impact of physical devices affects preferences. (Confidence: 0.5, Creative: 0.7)
8. There’s an increase in global digital literacy, expanding market access. (Confidence: 0.6, Creative: 0.6)
9. Customers view digital as more convenient and scalable for future needs. (Confidence: 0.7, Creative: 0.5)
10. Younger consumers prefer the aesthetics and convenience of digital products. (Confidence: 0.6, Creative: 0.6)

*Reflection:* 
"Have I considered all possible influences? Are there any surprising factors that could explain this shift?"

*Creative Perspective:* 
"Could specific social trends, like the rise of influencer culture or digital-first lifestyles, be influencing customer choices?"

**2.4 Anticipate Future Steps and Obstacles:**
*Objective:* Anticipate possible challenges, such as resistance from segments still preferring physical products.

*Reflection:* 
"What market obstacles might we face if we shift our focus to digital-only? Are there sub-segments that still prioritize physical products?"

*Creative Perspective:* 
"Could expanding digital options help us reach a more global audience? Are there emerging trends that we could leverage in our strategy?"

[end sys2]

[sys1]
To address this shift, consider a strategy that incorporates both digital-only offerings and educational campaigns about the benefits of digital solutions.
Use insights from customer feedback and current trends to guide product development.
Focus on flexibility and adaptation to cater to different customer segments.
[end sys1]


Q:

GDAL - Unable to convert to Web Mercator using gdalwarp

I am making geoTIFs of weather data (for a Mapbox overlay) and I am converting them to web mercator for use on the map. The images were generated from the same source file and both images have the same coordinates (files provided below). The first file below converts to Web Mercator perfectly and shows up in Mapbox exactly where it should be. The second file (according to the gdalinfo dump) converted to Web Mercator also - but the coordinates changed! Why is this and how do I fix it? The second file does not display properly on the map because of this.
Below are links to both geoTIF files and my script I used to convert.
KEWX_L2_REF.TIF -  1st original geoTIF file, it converts just fine
KEWX_L2_VEL.TIF This is the 2nd original geoTIF file, the one that won't convert without distorting coordinates
Here are the GDALINFO dumps :
KEWX_L2_REF.tif - Original
KEWX_L2_REF-projected.tif Projected (coordinates are good after conversion)
KEWX_L2_VEL.tif - Original
KEWX_L2_VEL-projected.tif - Projected (coordinates have changed for some reason, should match the REF file above
The scripts I am using for these are the following :
gdalwarp EPSG:3857 KEWX_L2_REF.tif KEWX_L2_REF-projected.tif

and 
gdalwarp EPSG:3857 KEWX_L2_VEL.tif KEWX_L2_VEL-projected.tif 

The original coordinates are identical and the scripts are identical (except for the filename of course) but I am trying not to rule anything out.
Is this something simple in the script that I should understand, what am I missing?

A:

I do not understand how you can get your results. I did nothing differently than you did, except added the -s_srsparameter. If that is not used your command is interpreted so that EPSG:3857 is the source image and that leads to error so I do not believe that you have really used your command literally like you wrote it into the question.
ERROR 4: EPSG:3857: No such file or directory

I used the images from your gdal.zip package.
Gdalinfo about the source images:
Driver: GTiff/GeoTIFF
Files: KEWX_L2_REF.tif
Size is 4000, 3500
Coordinate System is:
GEOGCS["WGS 84",
    DATUM["WGS_1984",
        SPHEROID["WGS 84",6378137,298.257223563,
            AUTHORITY["EPSG","7030"]],
        AUTHORITY["EPSG","6326"]],
    PRIMEM["Greenwich",0],
    UNIT["degree",0.0174532925199433],
    AUTHORITY["EPSG","4326"]]
Origin = (-102.000000000000000,33.000000000000000)
Pixel Size = (0.002000000000000,-0.002000000000000)
Corner Coordinates:
Upper Left  (-102.0000000,  33.0000000) (102d 0' 0.00"W, 33d 0' 0.00"N)
Lower Left  (-102.0000000,  26.0000000) (102d 0' 0.00"W, 26d 0' 0.00"N)
Upper Right ( -94.0000000,  33.0000000) ( 94d 0' 0.00"W, 33d 0' 0.00"N)
Lower Right ( -94.0000000,  26.0000000) ( 94d 0' 0.00"W, 26d 0' 0.00"N)
Center      ( -98.0000000,  29.5000000) ( 98d 0' 0.00"W, 29d30' 0.00"N)

Driver: GTiff/GeoTIFF
Files: KEWX_L2_VEL.tif
Size is 4000, 3500
Coordinate System is:
GEOGCS["WGS 84",
    DATUM["WGS_1984",
        SPHEROID["WGS 84",6378137,298.257223563,
            AUTHORITY["EPSG","7030"]],
        AUTHORITY["EPSG","6326"]],
    PRIMEM["Greenwich",0],
    UNIT["degree",0.0174532925199433],
    AUTHORITY["EPSG","4326"]]
Origin = (-102.000000000000000,33.000000000000000)
Pixel Size = (0.002000000000000,-0.002000000000000)
Corner Coordinates:
Upper Left  (-102.0000000,  33.0000000) (102d 0' 0.00"W, 33d 0' 0.00"N)
Lower Left  (-102.0000000,  26.0000000) (102d 0' 0.00"W, 26d 0' 0.00"N)
Upper Right ( -94.0000000,  33.0000000) ( 94d 0' 0.00"W, 33d 0' 0.00"N)
Lower Right ( -94.0000000,  26.0000000) ( 94d 0' 0.00"W, 26d 0' 0.00"N)
Center      ( -98.0000000,  29.5000000) ( 98d 0' 0.00"W, 29d30' 0.00"N)

Your commands which I re-used
gdalwarp -t_srs EPSG:3857 KEWX_L2_REF.tif KEWX_L2_REF-projected.tif
gdalwarp -t_srs EPSG:3857 KEWX_L2_REF.tif KEWX_L2_REF-projected.tif

Shortened gdalinfo about the resulting GeoTIFFs
Driver: GTiff/GeoTIFF
Files: KEWX_L2_REF-projected.tif
Size is 3746, 3770
Coordinate System is:
PROJCS["WGS 84 / Pseudo-Mercator",
....
    AUTHORITY["EPSG","3857"]]
Origin = (-11354588.060913905501366,3895303.963393894489855)
Pixel Size = (237.710730685124162,-237.710730685124162)
Corner Coordinates:
Upper Left  (-11354588.061, 3895303.963) (102d 0' 0.00"W, 33d 0' 0.00"N)
Lower Left  (-11354588.061, 2999134.509) (102d 0' 0.00"W, 26d 0' 1.56"N)
Upper Right (-10464123.664, 3895303.963) ( 94d 0' 2.96"W, 33d 0' 0.00"N)
Lower Right (-10464123.664, 2999134.509) ( 94d 0' 2.96"W, 26d 0' 1.56"N)
Center      (-10909355.862, 3447219.236) ( 98d 0' 1.48"W, 29d33'38.89"N)

Driver: GTiff/GeoTIFF
Files: KEWX_L2_VEL-projected.tif
Size is 3746, 3770
Coordinate System is:
PROJCS["WGS 84 / Pseudo-Mercator",
....
    AUTHORITY["EPSG","3857"]]
Origin = (-11354588.060913905501366,3895303.963393894489855)
Pixel Size = (237.710730685124162,-237.710730685124162)
Corner Coordinates:
Upper Left  (-11354588.061, 3895303.963) (102d 0' 0.00"W, 33d 0' 0.00"N)
Lower Left  (-11354588.061, 2999134.509) (102d 0' 0.00"W, 26d 0' 1.56"N)
Upper Right (-10464123.664, 3895303.963) ( 94d 0' 2.96"W, 33d 0' 0.00"N)
Lower Right (-10464123.664, 2999134.509) ( 94d 0' 2.96"W, 26d 0' 1.56"N)
Center      (-10909355.862, 3447219.236) ( 98d 0' 1.48"W, 29d33'38.89"N)