Estimating Dive Visibility from Satellite Chlorophyll Data

There's a question that every spearfisherman and freediver asks before a trip and nobody has a good answer to: what's the visibility going to be?

You can check the swell forecast. You can check the wind. You can look at the tide charts. But visibility? The best anyone can offer is “go look” or “call the dive shop.” I fish out of Oxnard, California and dive in southeast Asia. I've mostly avoided the visibility lottery for years by checking satellite chlorophyll data before I run out to the islands. Plenty of offshore guys already do this. But most people stop at reading the color map. There's actually a formula that puts a number on it.

It turns out the science for this has existed for decades. Satellites measure chlorophyll concentration in the ocean from space. Chlorophyll concentration has a well-documented inverse relationship with underwater visibility. And you can express that relationship with a single formula. This is the story of that formula, where it comes from, what it can tell you, and where it lies to you.

The Secchi Disk: 160 Years of Staring Into Water

In 1865, an Italian Jesuit priest and astronomer named Pietro Angelo Secchi was aboard the papal yacht L'Immacolata Concezione in the Mediterranean. Commander Alessandro Cialdi, head of the Papal Navy, had asked Secchi to help develop a standardized way to measure water transparency. Secchi lowered a white disk into the water on a rope. He kept lowering it until he couldn't see it anymore. He wrote down the depth. That was the measurement.

It's almost comically simple. And it's still the global standard for measuring water transparency 160 years later. There have been fancier instruments. Transmissometers. Spectroradiometers. Satellite-derived attenuation coefficients. But scientists still drop white disks on ropes into the ocean because it works and because we have a century of data collected the same way.

The interesting question is: what's actually happening physically when the disk disappears?

In 1968, J.E. Tyler worked this out. He applied the contrast transmittance theory developed by Duntley and Preisendorfer to show that the disappearance depth is governed by two optical properties of the water column: the beam attenuation coefficient (c) and the diffuse attenuation coefficient (K_d). The first describes how a directed beam of light gets scattered and absorbed. The second describes how the overall downward light field attenuates with depth. Together they determine how much contrast remains between the white disk and the surrounding water at any given depth.

Tyler's result:

The 8.69 isn't arbitrary. It falls out of the physics of contrast perception. When a white disk is submerged, its apparent contrast against the surrounding water decreases exponentially with depth. The disk disappears when that contrast drops below the detection threshold of the human eye. The constant 8.69 encodes the full contrast equation: the ratio of the disk's inherent contrast (driven by the reflectance difference between the white disk and the surrounding water) to the minimum contrast a human observer can detect. Tyler derived it assuming a disk reflectance of about 80% and a water reflectance of about 2%.

One thing to note: Secchi depth is a measure of vertical water transparency, not horizontal diver visibility. Divers usually think about how far they can see horizontally. The two are related, because both depend on the same optical properties of the water column, but they're not the same measurement. Secchi depth is best understood as a proxy for overall water clarity rather than a direct prediction of what a diver will experience at depth. Throughout this article, when I refer to “estimated visibility,” I mean it in that proxy sense.

The Connection to Chlorophyll

Tyler's formula gives you Secchi depth if you know the optical coefficients. But measuring c and K_d requires putting instruments in the water. The breakthrough for remote sensing came from André Morel.

In a 1988 paper that became foundational to ocean color science, Morel showed that in open ocean waters, the optical properties of the water column are dominated by one thing: phytoplankton. More specifically, the chlorophyll-a pigment inside phytoplankton cells. The cells absorb light (especially in the blue wavelengths, which is why chlorophyll-rich water looks green) and they scatter light. Both of these effects increase c and K_d, which decreases Secchi depth.

Morel called these “Case 1” waters. Waters where phytoplankton is the primary driver of optical properties. In Case 1 conditions, if you know the chlorophyll concentration, you can estimate the attenuation coefficients. And if you can estimate the attenuation coefficients, you can estimate the Secchi depth. The chain is: chlorophyll to optics to visibility.

This matters because satellites can measure chlorophyll. Instruments like VIIRS (on NOAA's polar-orbiting satellites) and MODIS (on NASA's Aqua satellite) measure the color of light reflected from the ocean surface. The ratio of blue to green reflectance tells you the chlorophyll concentration. This has been validated extensively against ship-based measurements across the global ocean.

The Formula

When you combine Morel's bio-optical model with Tyler's contrast theory, you get a power law relationship between chlorophyll and Secchi depth. Multiple research groups have fitted this relationship against field data. The general form is:

The coefficients A and B vary by study and region, but they converge. The power law shape makes intuitive sense. Going from 0.1 to 0.2 mg/m³ chlorophyll has a larger effect on visibility than going from 5.0 to 5.1. The relationship is nonlinear because light attenuation compounds with depth.

The implementation we use in Chlorofishy:

This is a practical estimation model, not a first-principles identity. The constant 8.69 comes from Tyler's contrast theory. The exponent -0.47 is an empirical fit to published datasets relating chlorophyll to measured Secchi depth in Case 1 waters. Different researchers using different ocean basins get slightly different coefficients. We chose values that are well-supported by the literature and consistent with the Morel bio-optical framework, but this is a calibrated approximation, not a derivation from physics alone.

Here's what that looks like across a range of chlorophyll values:

The range that matters most for spearfishing and freediving is roughly 0.2 to 2.0 mg/m³. That's the range where the difference between a good day and a wasted trip lives. And it's the range where the formula has the best predictive power.

But I want to be clear about what this number represents. The Secchi estimate is a best-case ceiling. It tells you what visibility would be if phytoplankton were the only thing in the water column. In reality, there's almost always something else: suspended sediment, dissolved organic matter, wave-churned particles. Actual visibility will typically be equal to or less than the Secchi estimate. Think of it as the upper bound on what's possible given the biology.

In practice, the formula runs optimistic. From years of comparing chlorophyll charts to what I actually find in the water around the Channel Islands, readings of 0.5 mg/m³ and under generally mean decent visibility, maybe 30 to 40 feet. Once you get up toward 0.9 or 1.0, things deteriorate noticeably, often under 20 feet. The formula would predict higher numbers for both. The difference is everything else in the water that isn't phytoplankton.

The takeaway isn't that the formula is wrong. It's that the Secchi estimate is a ceiling and the actual floor depends on your specific conditions. What stays consistent is the ranking. Lower chlorophyll generally means better visibility. The relative comparison between days, between sites, between satellite passes is where the real value is.

Chlorophyll Data Without the Formula

Here's something worth saying: the chlorophyll chart is useful even if you never look at the Secchi number. Every diver and offshore angler who has spent time with satellite chlorophyll data develops the same intuition. Bluer areas on the chart mean cleaner water. Greener areas mean more phytoplankton, which means murkier water. You don't need a formula to read that. A quick glance at the color gradient tells you where the cleaner water is relative to the dirtier water, and that relative information is valuable on its own.

The Secchi formula adds a quantitative layer on top of that intuition. It converts “greener than yesterday” into “roughly 8 meters instead of 14.” For some people that's the difference between going and not going. For others the color map alone is enough.

Why This Matters for Hook-and-Line Fishing

Visibility isn't just a spearfishing concern. For hook-and-line anglers, water clarity changes the entire tactical picture.

In clear water, fish see everything. Your line, your leader, your knots. This is where finesse matters. Fluorocarbon leaders become essential because their refractive index is close to water, making them nearly invisible. Leader lengths go up to 36 inches or more. Lure presentations need to look natural. Colors should be subtle and realistic. You're fishing against a fish that can see you coming.

In murkier water, the game changes. You can get away with heavier leaders because the fish can't see them as easily. Darker lure colors that create contrast against the background become more effective than natural colors. Presentations that generate vibration and noise, like paddle tails, chatterbaits, and poppers, outperform subtle presentations because fish are relying more on their lateral line than their eyes. Scented baits get more productive because smell becomes a primary sense when vision is limited.

What's interesting from a predator behavior standpoint is that moderate turbidity can actually improve fishing. Many gamefish are ambush predators. They use reduced visibility as cover to position themselves near cleaner water and strike prey that can't see them coming. The mixing zone between clean and murky water, the “color break,” functions as structure in the same way a temperature break does. Predators patrol it. Bait concentrates along it. It's a seam in the ocean and fish know it.

Knowing the clarity gradient before you leave the dock tells you what to rig. If the satellite is showing clean blue water over your spot, go light. Fluorocarbon leader, natural colors, finesse. If it's showing a plankton bloom or green water pushing through, rig heavier, go darker, bring the noisy stuff. You're not guessing anymore. You're reading the water before you can see it.

The Validity Domain

This is where I need to be precise about what we're claiming.

The Morel framework, and by extension our formula, was developed for and validated in Case 1 waters. Morel and Prieur proposed this classification in 1977. Case 1 waters are those where phytoplankton and its co-varying degradation products are the dominant influence on optical properties. This is most of the open ocean. It's the blue water offshore. It's the water around islands and reefs once you're away from river outflows and sediment plumes.

If you're planning a boat dive to an offshore spot, checking conditions around the Channel Islands, or looking at water quality 10+ miles from the coast, this estimate is solid. The chain from satellite chlorophyll to Secchi depth has been validated by multiple independent research groups using in situ matchup datasets. Doron et al. (2011) compiled over 400 satellite-vs-field matchups and found R² values between 0.50 and 0.73 depending on the algorithm and sensor. That's not perfect. But it's useful.

Where the Model Fails

The formula fails in “Case 2” waters. These are coastal and near-shore waters where things other than phytoplankton dominate the optical properties. Sediment from river runoff after rain. Dissolved organic matter from estuaries. Resuspended sand and silt from wave action on the bottom. Kelp particles and detritus.

All of these reduce visibility independently of chlorophyll concentration. The satellite reads chlorophyll at 0.3 mg/m³ and the formula says “18 meters visibility.” But the actual vis is 3 meters because there's a sediment plume from two days of rain that has nothing to do with phytoplankton. Standard ocean color algorithms do not reliably disentangle light attenuation from phytoplankton and light attenuation from suspended sediment. They both make the water greener. But they mean different things for the formula's validity.

This is the fundamental limitation of this approach, and current satellite ocean color sensors don't offer a clean solution for it in coastal waters.

Other Failure Modes

Depth structure. The satellite measures the surface. Specifically, it measures the color of light emerging from roughly the top optical depth of the water column. It tells you nothing about what's happening below a thermocline. Any diver who's dropped through a thermocline and watched the world change from green haze to blue clarity knows this. The estimate is a surface estimate. Subsurface conditions can be completely different.

Temporal aliasing. A satellite pass captures one moment. Currents move water. Upwelling events can change chlorophyll concentrations in hours. Wind shifts can push clean water onshore or pile dirty water against the coast. A reading from this morning may not represent conditions this afternoon. And if clouds have blocked the sensor for days, your most recent data might be 48 or 72 hours stale. This is one of the problems that motivated me to build Chlorofishy. Most satellite services paper over cloud gaps with modeled or composited data and present it as current. We show you the actual cloud gaps. If the satellite couldn't see your spot, we tell you that instead of guessing.

Spatial resolution. The chlorophyll sensors we use (VIIRS on S-NPP, NOAA-20, and NOAA-21, plus MODIS on Aqua) have native resolutions ranging from 750 meters to 4 kilometers depending on the product. A localized pocket of dirty water at your specific dive site won't show up if the pixel it falls in is mostly clean. The estimate is an average over that pixel area.

Empirical coefficients. The exponent -0.47 and the constant 8.69 are derived from fitting large datasets across multiple ocean basins. Your specific region may deviate. Waters with high background CDOM (colored dissolved organic matter), like much of the Baltic or some tropical river-influenced coasts, will show a systematic bias. The formula will overestimate visibility in those areas because there's an additional light-absorbing component that doesn't covary with chlorophyll.

Why We Implemented This

Every satellite fishing service shows chlorophyll as a colored overlay on a map. The number they give you is in mg/m³. That's useful if you're a marine biologist. It's useless if you're a diver trying to decide whether to make the drive.

We run the conversion so you don't have to. Click anywhere on the ocean in Chlorofishy and the chlorophyll readout includes an estimated Secchi depth in meters and feet. Same satellite data everyone else shows you. One extra step of math that makes it actionable.

We present it as an estimate. The platform tells you which satellite captured the data, when, at what resolution, and whether it's a raw pass or a gap-filled composite. If the data is stale, you'll know. If there are cloud gaps, you'll see them. The whole point of Chlorofishy is that you should know exactly what you're looking at and how much to trust it.

Practical Application

The night before a dive, I check swell and wind like everyone else. Then I open Chlorofishy and look at the latest chlorophyll pass for my area. I click a few spots near where I'm planning to go. If the Secchi estimate reads 15+ meters and conditions are clean, I'm going. If it's showing 5 to 7 meters with a visible bloom over my spot, I either pick a different site or save my fuel money.

I also compare passes from consecutive days. If chlorophyll is trending down, conditions are probably improving as a bloom dissipates. If it's trending up, things are getting worse. The temporal dimension is as valuable as the point measurement.

None of this replaces getting in the water and looking. But it's one more piece of information in the decision. And in my experience, once you're a few miles offshore where Case 1 conditions dominate, it's a pretty good piece of information.

It's the same read I use for tracking yellowtail pushes: see Migrants and Mossbacks: The Two Lives of the California Yellowtail for how water clarity and temperature play out on a specific fish. The clearest water I fish regularly is off the Florida Keys, and our ocean water clarity map runs the same estimate shown here for any region, updated daily.