Add ezuetell preliminary analysis of QDM method in May forecast

a08_qdm_may.ipynb

@@ -0,0 +1,89 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "39e0f601",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import xarray as xr\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7e124e2e",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "44d3a33c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "forecast_qdm = xr.open_dataset(\"gs://poreallas-public-20260605/v20260731/parsed/forecast_adj.zarr\", engine = 'zarr', backend_kwargs = {\"storage_options\": {\"token\": \"anon\"}},)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "e54dfb1c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/emily_zuetell/git_projects/poreallas/.venv/lib/python3.14/site-packages/zarr/api/asynchronous.py:231: ZarrUserWarning: Consolidated metadata is currently not part in the Zarr format 3 specification. It may not be supported by other zarr implementations and may change in the future.\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<xarray.backends.zarr.ZarrStore at 0x7d967006cae0>"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "forecast_qdm.to_zarr(\"forecast_qdm.zarr\", mode = \"w\", consolidated = True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cece8d92",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "poreallas-env (3.14.4.final.0)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.14.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

analysis/isku_utils.py

@@ -38,6 +38,9 @@ def read_regions(uri: str) -> isku.GridWeightingRegions:
     return regions
 
 def grid_to_ir(data, savefile = None):
+    if 'longitude' in data.dims:
+        if data['longitude'].min() >= 0:
+            data = lon_adjust(data)
     regions = read_regions(REGIONS_URI)
     data_ir = isku.extract_regions(
         data,
@@ -48,3 +51,10 @@ def grid_to_ir(data, savefile = None):
     if savefile is not None:
         data_ir.to_zarr(f"{savefile}.zarr")
     return data_ir
+
+def lon_adjust(_ds):
+    _ds["longitude"] = (_ds["longitude"] + 180) % 360 - 180
+    _ds = _ds.sortby("longitude")
+    _ds = _ds.rename({"longitude": "lon", "latitude": "lat"})
+    _ds = _ds.chunk("auto")
+    return _ds