Leveraging remote sensing and forecasting to better understand an unpredictable climate

Learn how Lens and HydroForecast can assist with planning efforts during non-average weather years like 2023.

Jun 1, 2023
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For those looking to keep score: the West is indeed drier than ever while also receiving record amounts of snow this year. How? Well, our old friend climate change is back on the scene, and so are we.

Despite California’s current infamy of drought and wildfires, the state this year averaged about 200% snowpack of a “normal” year. This is undoubtedly great. Snowpack eventually melts and drains into California reservoirs, where it’s then used for a variety of reasons: potable water, agricultural needs, industrial use, and to provide electricity through hydropower. In an average year, snowpack from California’s Eastern mountains accounts for about one-third of the state’s total freshwater supply.

However, no change in climate activity arrives so simply. One contributing factor to the unusually high snowpack year is the number of severe storms that California experienced, most of which were caused by atmospheric rivers. An atmospheric river is a corridor of moisture in the atmosphere, which brings both accumulated snowpack and high levels of runoff from the tropical moisture.

The frequency of atmospheric rivers is increasing over time due to the complex interactions between the atmosphere and our warming ocean.1 According to Scripps Institute of Oceanography, an incredible 17 atmospheric rivers have hit California since December 2022.

Therein lies the problem: the duo are a force to be reckoned with, especially under our changing climate.

High snowpack plus the intensity of atmospheric rivers can lead to severe flooding, which causes many forms of damage: financial, social, and of course, environmental. On top of that, flooding is typically more consequential in areas that have been experiencing drought for the last several years because water can’t saturate the ground as easily. The result this year? Estimates indicate that floods from storms in California this winter caused more than $30 billion in property damages and economic losses.2

While there is a positive side to this, namely that these levels of snowpack have also refilled some state reservoirs, contributed to groundwater recharge, and filled water banks, the question remains: how do we handle these discrepancies? Where do we go from here?

Data to fill the missing links

As our changing climate increases these non-average weather years, the need for readily accessible environmental data is crucial. Environmental data can provide a window into past historical trends, current environmental conditions, and it can provide foresight into the future, which is essential for resource management, planning, and minimizing damages.

HydroForecast and Lens fill just that gap.

Using Lens and HydroForecast to prepare for a high-snowpack year

Let’s take a look at Trinity River Basin in California as an example.

Lens provides valuable insights regarding current conditions and historical trends in information such as snowpack levels. The plot below illustrates how snowpack this year compares to recent years. In short: snow this year persisted longer into the spring than any other in the past several years.

Why is this important? Understanding the current state of a river basin is critical in quantifying the amount of snow that will contribute to streamflow throughout the remainder of the year.

Figure 1. Sentinel-2 snow index layer from January - June of 2021 (pink), 2022 (blue) and 2023 (orange), via Lens.

Last year on April 30th, the Trinity River basin’s snow index, or percent coverage in snow, was 24%. On the same day this year, it was 47%. That’s a 196% increase from the year prior.

Figure 2. Trinity River basin snow coverage 4/30/2022 (left) vs. 4/30/2023 (right) via Lens. Copyright Planet Labs PBC.

The plot below shows the difference in snow between the end of March this year and the end of April. All the snow that melts in this basin ends up flowing down the Trinity River into Trinity Lake near Mount Shasta in California, one of the state’s many reservoirs.

Figure 3. Trinity River basin snow coverage 3/31/2023 (left) vs. 4/30/2023 (right) via Lens. Copyright Planet Labs PBC.

After taking a look at how Lens can give us a deep understanding of the Trinity River basin, let’s see how HydroForecast can provide additional information on the potential future impact of the high snowpack.

HydroForecast takes inputs from various weather sources and snowpack and vegetation satellite observations and predicts streamflow days and even months into the future. This allows users to optimize their water resources and plan for flooding events, especially during non-average years like the one California just experienced.

HydroForecast also displays surface observations averaged over a given forecast point’s basin, giving users information around the amount of snow left to melt and how it compares to previous years. The plot below shows snow water equivalent in the Trinity River basin over the last 12 months. We can see that the snowpack as of the end of May 2023 is 382% of the historical average. These data points help users understand how the remainder of a given water year will compare to previous water years, and how their decision making may need to change in terms of planning for water allocation and flood management.

Figure 4. Snow Water Equivalent (SWE) across the Trinity River basin via HydroForecast.

The following plot shows a past forecast from HydroForecast Short-term capturing snowmelt activity days before it happened. The black line indicates observed values. The daily fluctuations represent the diurnal freezing as the snow melts.

Figure 5. Inflow forecast into Trinity Lake from April 9th, 2023 via HydroForecast.

HydroForecast Short-term flow forecasts predict flow 10 days into the future. HydroForecast Seasonal can predict flow 12 months into the future, and our newest product, HydroForecast Long-term predicts hydrologic scenarios out to 2100.


With our warming climate, extreme weather years are becoming the norm, making the need for better access to environmental data more crucial now than ever. With HydroForecast’s machine learning model that predicts streamflow and Lens’s platform that makes geospatial data easily accessible, we can more deeply understand the natural environment and anticipate and plan for the impacts that extreme weather and climate change are causing.

To learn more about our products, follow these hyper-links to get in touch with our HydroForecast team and our Lens team.

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  1. Berwyn, Bob. “Relentless rise of ocean heat content drives deadly extremes.” Inside Climate News, 11 January 2023
  2. Sullivan, Bryan. “California storm losses estimated at more than $30 billion.”, 12 January 2023