{ "cells": [ { "cell_type": "markdown", "id": "70e3fb74", "metadata": {}, "source": [ "# QIQ 2024 full year: QC, REST2 clear-sky, and four separation models\n", "\n", "This tutorial **loops over twelve** BSRN station-to-archive files (`qiq0124.dat.gz` … `qiq1224.dat.gz`), concatenates them, runs **`run_qc`**, adds **REST2** clear-sky columns via **`add_clearsky_columns`** (MERRA-2 inputs from Hugging Face), then runs **Erbs**, **BRL**, **Engerer2**, and **Yang4** separation and plots **`k` vs `k_t`** with **`plot_k_vs_kt`**.\n" ] }, { "cell_type": "markdown", "id": "25e14db7", "metadata": {}, "source": [ "## Prerequisites\n", "\n", "- All **12** files under `data/QIQ/` for 2024 (see `data/download_qiq_2024.py` or tutorial 1).\n", "- **Network** access for **REST2** (first run downloads MERRA-2 parquet per month from Hugging Face).\n", "- **`pip install 'bsrn[viz]'`** (plotnine, matplotlib) for the figure.\n", "- Set **`REPO_ROOT`** in the next cell to your local clone (absolute path).\n" ] }, { "cell_type": "code", "execution_count": 1, "id": "2de7ddab", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "REPO_ROOT: /Volumes/Macintosh Research/Data/bsrn-qc\n", "DATA_DIR: /Volumes/Macintosh Research/Data/bsrn-qc/data/QIQ\n", "Station: QIQ 47.7957 124.4852 170.0\n" ] } ], "source": [ "from __future__ import annotations\n", "\n", "from pathlib import Path\n", "\n", "import pandas as pd\n", "\n", "from bsrn.constants import BSRN_STATIONS\n", "from bsrn.io.reader import read_station_to_archive\n", "from bsrn.modeling.clear_sky import add_clearsky_columns\n", "from bsrn.modeling.separation import (\n", " brl_separation,\n", " engerer2_separation,\n", " erbs_separation,\n", " yang4_separation,\n", ")\n", "from bsrn.qc.wrapper import run_qc\n", "from bsrn.visualization.separation import plot_k_vs_kt\n", "\n", "REPO_ROOT = Path(\"/Volumes/Macintosh Research/Data/bsrn-qc\")\n", "DATA_DIR = REPO_ROOT / \"data\" / \"QIQ\"\n", "STATION_CODE = \"QIQ\"\n", "YEAR_SUFFIX = \"24\" # 2024 -> qiqMM24.dat.gz\n", "\n", "meta = BSRN_STATIONS[STATION_CODE]\n", "lat, lon, elev = meta[\"lat\"], meta[\"lon\"], meta[\"elev\"]\n", "\n", "print(\"REPO_ROOT:\", REPO_ROOT)\n", "print(\"DATA_DIR: \", DATA_DIR)\n", "print(\"Station: \", STATION_CODE, lat, lon, elev)\n" ] }, { "cell_type": "markdown", "id": "f647e871", "metadata": {}, "source": [ "## 1. Load twelve monthly files\n", "\n", "Skip any month that is missing on disk (with a warning).\n" ] }, { "cell_type": "code", "execution_count": 2, "id": "7f70c875", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Loaded qiq0124.dat.gz rows=44,640\n", "Loaded qiq0224.dat.gz rows=41,760\n", "Loaded qiq0324.dat.gz rows=44,640\n", "Loaded qiq0424.dat.gz rows=43,200\n", "Loaded qiq0524.dat.gz rows=44,640\n", "Loaded qiq0624.dat.gz rows=43,200\n", "Loaded qiq0724.dat.gz rows=44,640\n", "Loaded qiq0824.dat.gz rows=44,640\n", "Loaded qiq0924.dat.gz rows=43,200\n", "Loaded qiq1024.dat.gz rows=44,640\n", "Loaded qiq1124.dat.gz rows=43,200\n", "Loaded qiq1224.dat.gz rows=44,640\n", "\n", "Concatenated: 527,040 rows 2024-01-01 00:00:00+00:00 … 2024-12-31 23:59:00+00:00 UTC\n" ] } ], "source": [ "chunks: list[pd.DataFrame] = []\n", "missing: list[str] = []\n", "\n", "for month in range(1, 13):\n", " name = f\"{STATION_CODE.lower()}{month:02d}{YEAR_SUFFIX}.dat.gz\"\n", " path = DATA_DIR / name\n", " if not path.is_file():\n", " missing.append(name)\n", " continue\n", " sub = read_station_to_archive(str(path), logical_records=\"lr0100\")\n", " if sub is None or sub.empty:\n", " missing.append(f\"{name} (empty or read failed)\")\n", " continue\n", " chunks.append(sub)\n", " print(f\"Loaded {name} rows={len(sub):,}\")\n", "\n", "if missing:\n", " print(\"WARNING — skipped:\", \", \".join(missing))\n", "if not chunks:\n", " raise FileNotFoundError(\n", " f\"No monthly files found under {DATA_DIR}. \"\n", " \"Download QIQ 2024 archives first (e.g. data/download_qiq_2024.py).\"\n", " )\n", "\n", "df = pd.concat(chunks, axis=0)\n", "df = df[~df.index.duplicated(keep=\"first\")].sort_index()\n", "print(f\"\\nConcatenated: {len(df):,} rows {df.index.min()} … {df.index.max()} UTC\")\n" ] }, { "cell_type": "markdown", "id": "e922a747", "metadata": {}, "source": [ "## 2. Quality control + REST2 clear-sky\n", "\n", "**`run_qc`** adds `flag*` columns (same pipeline as tutorial 2). **`add_clearsky_columns`** with **`model='rest2'`** adds `ghi_clear`, `bni_clear`, `dhi_clear` using MERRA-2 (may take a few minutes the first time). After clear-sky, we **subset** the frame to rows with **all flags 0** (pass) and **solar zenith ≤ 85°** (exclude low-sun geometry).\n" ] }, { "cell_type": "code", "execution_count": 3, "id": "bf7cd9e3", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "QC flags: ['flagPPLGHI', 'flagPPLBNI', 'flagPPLDHI', 'flagPPLLWD', 'flagERLGHI', 'flagERLBNI'] ...\n", "Fetching MERRA-2 from Hugging Face: qiq/qiq0124_merra2.parquet\n", "Fetching MERRA-2 from Hugging Face: qiq/qiq0224_merra2.parquet\n", "Fetching MERRA-2 from Hugging Face: qiq/qiq0324_merra2.parquet\n", "Fetching MERRA-2 from Hugging Face: qiq/qiq0424_merra2.parquet\n", "Fetching MERRA-2 from Hugging Face: qiq/qiq0524_merra2.parquet\n", "Fetching MERRA-2 from Hugging Face: qiq/qiq0624_merra2.parquet\n", "Fetching MERRA-2 from Hugging Face: qiq/qiq0724_merra2.parquet\n", "Fetching MERRA-2 from Hugging Face: qiq/qiq0824_merra2.parquet\n", "Fetching MERRA-2 from Hugging Face: qiq/qiq0924_merra2.parquet\n", "Fetching MERRA-2 from Hugging Face: qiq/qiq1024_merra2.parquet\n", "Fetching MERRA-2 from Hugging Face: qiq/qiq1124_merra2.parquet\n", "Fetching MERRA-2 from Hugging Face: qiq/qiq1224_merra2.parquet\n", "REST2 columns added; ghi_clear sample: 560.3791024928188\n", "Filtered 527,040 → 235,581 rows (all QC flags 0, zenith ≤ 85°)\n" ] } ], "source": [ "from bsrn.physics import geometry\n", "\n", "run_qc(df, station_code=STATION_CODE)\n", "print(\"QC flags:\", [c for c in df.columns if c.startswith(\"flag\")][:6], \"...\")\n", "\n", "df = add_clearsky_columns(df, station_code=STATION_CODE, model=\"rest2\")\n", "print(\"REST2 columns added; ghi_clear sample:\", float(df[\"ghi_clear\"].iloc[len(df) // 2]))\n", "\n", "n_before = len(df)\n", "flag_cols = [c for c in df.columns if c.startswith(\"flag\")]\n", "qc_ok = (\n", " (df[flag_cols] == 0).all(axis=1)\n", " if flag_cols\n", " else pd.Series(True, index=df.index)\n", ")\n", "zenith = geometry.get_solar_position(df.index, lat, lon, elev)[\"zenith\"]\n", "sun_ok = zenith <= 85.0\n", "df = df.loc[qc_ok & sun_ok]\n", "print(f\"Filtered {n_before:,} → {len(df):,} rows (all QC flags 0, zenith ≤ 85°)\")\n" ] }, { "cell_type": "markdown", "id": "0c79d0fe", "metadata": {}, "source": [ "## 3. Four separation models\n", "\n", "Store model diffuse fraction **`k`** in columns for **`plot_k_vs_kt`**. Engerer2 uses **`averaging_period=1`** for 1-minute data.\n" ] }, { "cell_type": "code", "execution_count": 4, "id": "2345b086", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "k columns OK; non-NaN counts:\n", " k_erbs: 235,581\n", " k_brl: 235,581\n", " k_engerer2: 235,581\n", " k_yang4: 235,581\n" ] } ], "source": [ "times = df.index\n", "ghi = df[\"ghi\"].to_numpy(dtype=float)\n", "\n", "df[\"k_erbs\"] = erbs_separation(times, ghi, lat, lon, elev=elev)[\"k\"]\n", "df[\"k_brl\"] = brl_separation(times, ghi, lat, lon)[\"k\"]\n", "df[\"k_engerer2\"] = engerer2_separation(\n", " times, ghi, lat, lon, df[\"ghi_clear\"].to_numpy(dtype=float), averaging_period=1\n", ")[\"k\"]\n", "df[\"k_yang4\"] = yang4_separation(\n", " times, ghi, lat, lon, df[\"ghi_clear\"].to_numpy(dtype=float)\n", ")[\"k\"]\n", "\n", "print(\"k columns OK; non-NaN counts:\")\n", "for c in (\"k_erbs\", \"k_brl\", \"k_engerer2\", \"k_yang4\"):\n", " print(f\" {c}: {df[c].notna().sum():,}\")\n" ] }, { "cell_type": "markdown", "id": "ac531bf8", "metadata": {}, "source": [ "## 4. `k` vs `k_t` plot\n", "\n", "Faceted density plot (measured gray + model viridis), **160 mm** wide per project style.\n" ] }, { "cell_type": "code", "execution_count": 5, "id": "2e1cad63", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Saved: /Volumes/Macintosh Research/Data/bsrn-qc/_tmp_QIQ_2024_separation_k_kt.pdf\n" ] }, { "data": { "image/png": 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", "text/plain": [ "" ] }, "execution_count": null, "metadata": {}, "output_type": "execute_result" } ], "source": [ "k_mod_cols = {\n", " \"erbs\": \"k_erbs\",\n", " \"brl\": \"k_brl\",\n", " \"engerer2\": \"k_engerer2\",\n", " \"yang4\": \"k_yang4\",\n", "}\n", "\n", "title = f\"{STATION_CODE} 2024 — k vs k_t (Erbs, BRL, Engerer2, Yang4; REST2 GHIC)\"\n", "out_pdf = REPO_ROOT / f\"_tmp_{STATION_CODE}_2024_separation_k_kt.pdf\"\n", "\n", "p = plot_k_vs_kt(\n", " df,\n", " models=(\"erbs\", \"brl\", \"engerer2\", \"yang4\"),\n", " lat=lat,\n", " lon=lon,\n", " ghi_col=\"ghi\",\n", " dhi_col=\"dhi\",\n", " k_mod_cols=k_mod_cols,\n", " title=title,\n", " output_file=str(out_pdf),\n", ")\n", "print(\"Saved:\", out_pdf)\n", "p\n" ] } ], "metadata": { "kernelspec": { "display_name": "base", "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": "3.13.9" } }, "nbformat": 4, "nbformat_minor": 5 }