Optimizing Grid Point Selection in ERA-Interim for Land Areas: A Comprehensive Guide

Decoding ERA-Interim for Land Studies: A Human’s Guide to Grid Points

Remember ERA-Interim? For years, it was the go-to dataset for climate and weather research. Think of it as a global weather puzzle, pieced together by the clever folks at the European Centre for Medium-Range Weather Forecasts (ECMWF). It ran from 1979 to August 2019, giving us a consistent look at the world’s weather patterns by blending model predictions with actual observations. Now, ERA-Interim has passed the baton to the newer, shinier ERA5. But, hey, understanding ERA-Interim is still super useful, especially if you’re digging into older projects or datasets. So, let’s talk about getting the most out of it, specifically when you’re focusing on land areas.

Cracking the Code: ERA-Interim’s Grid

ERA-Interim used a grid system, like a virtual checkerboard laid over the Earth. Each square, or grid point, covered about 80 km x 80 km. That’s pretty big! Now, here’s the thing: when you’re studying land, you’ve got to remember that each of those squares might be a mix of land and water, especially near the coasts. It’s like trying to figure out how much pizza topping you’re getting when some of it slid off the crust!

Land Ahoy! Picking the Right Grid Points

So, how do you grab only the land bits, or at least deal with those mixed land-water squares? Here are a few tricks I’ve picked up:

Pro Tips for Grid Point Ninjas

• Resolution Real Talk: 80 km is pretty chunky. Small islands? Narrow strips of land? ERA-Interim might not see them clearly. A grid point could be labeled “ocean” even if there’s some land hiding in there.
• Coastal Chaos: Coasts are tricky! Grid points there are often a land-water smoothie. Land-sea masking is essential to avoid your land data getting a fishy flavor.
• Interpolation Caveats: Need finer resolution? Interpolation can help, but it’s not magic. It can introduce errors, especially in rough terrain or near the coast. Be careful!
• Know Your Data: Some parameters are hourly, some are daily. Some are forecasts, some are analyses. Get familiar with the data structure before you start grabbing grid points willy-nilly.
• Bias Beware: ERA-Interim is awesome, but it’s not perfect. It has biases. If you’re doing something super sensitive, you might need to correct those biases. Compare ERA-Interim to local observations and adjust accordingly.

The Future is Now: ERA5 and ERA5-Land

Okay, let’s be real: ERA5 and ERA5-Land are the new kids on the block. ERA5 boasts a higher resolution (31 km) and hourly data. ERA5-Land cranks up the land surface resolution to a crazy-sharp 9 km! If you can, switch to these datasets. They’re just better. That said, the grid point wisdom I’ve shared still applies!

Final Thoughts

Picking the right ERA-Interim grid points for land studies is all about knowing the dataset’s quirks, dealing with those pesky mixed land-water areas, and matching your methods to your research goals. Use those land-sea masks, be wary of coastal zones, and remember that ERA-Interim has limitations. While ERA5 and ERA5-Land are the future, mastering these techniques will set you up for success with any gridded climate data. Happy analyzing!