Update README.md

README.md

@@ -80,13 +80,13 @@ Hugging Face: 3/16/2026 [URL](https://huggingface.co/nvidia/healda)
 
 - Output grid: HEALPix HPX64 (Nside=64), 49,152 pixels, \~1° (\~100 km) resolution
 - Output is regridded to 0.25° (721x1440) for downstream forecast model initialization
-- Output state variables: `u10m`, `v10m`, `u100m`, `v100m`, `t2m`, `msl`, `tcwv`, `sst`, `sic`,
-`u50`, `u100`, `u150`, `u200`, `u250`, `u300`, `u400`, `u500`, `u600`, `u700`, `u850`,
-`u925`, `u1000`, `v50`, `v100`, `v150`, `v200`, `v250`, `v300`, `v400`, `v500`, `v600`, `v700`, `v850`,
-`v925`, `v1000`, `z50`, `z100`, `z150`, `z200`, `z250`, `z300`, `z400`, `z500`, `z600`, `z700`, `z850`,
-`z925`, `z1000`, `t50`, `t100`, `t150`, `t200`, `t250`, `t300`, `t400`, `t500`, `t600`, `t700`, `t850`,
-`t925`, `t1000`, `q50`, `q100`, `q150`, `q200`, `q250`, `q300`, `q400`, `q500`, `q600`, `q700`, `q850`,
-`q925`, `q1000`
+- Output state variables: `u1000`, `u925`, `u850`, `u700`, `u600`, `u500`, `u400`, `u300`, `u250`, `u200`,
+`u150`, `u100`, `u50`, `v1000`, `v925`, `v850`, `v700`, `v600`, `v500`, `v400`, `v300`,
+`v250`, `v200`, `v150`, `v100`, `v50`, `t1000`, `t925`, `t850`, `t700`, `t600`, `t500`,
+`t400`, `t300`, `t250`, `t200`, `t150`, `t100`, `t50`, `z1000`, `z925`, `z850`, `z700`,
+`z600`, `z500`, `z400`, `z300`, `z250`, `z200`, `z150`, `z100`, `z50`, `q1000`, `q925`,
+`q850`, `q700`, `q600`, `q500`, `q400`, `q300`, `q250`, `q200`, `q150`, `q100`, `q50`,
+`tcwv`, `t2m`, `u10m`, `v10m`, `u100m`, `v100m`, `msl`, `sst`, `sic`
 
 Our AI models are designed and/or optimized to run on NVIDIA GPU-accelerated systems. By leveraging NVIDIA's hardware (e.g. GPU cores) and software frameworks (e.g., CUDA libraries), the model achieves faster training and inference times compared to CPU-only solutions.