From 2a49188848c669251909b5c21962b5f7e2c96c79 Mon Sep 17 00:00:00 2001 From: isilber Date: Thu, 10 Jul 2025 14:35:39 +0000 Subject: [PATCH 1/2] ENH: Intro to PrecipBE --- VAPs/precipbe/precipbe_intro.ipynb | 9221 ++++++++++++++++++++++++++++ 1 file changed, 9221 insertions(+) create mode 100644 VAPs/precipbe/precipbe_intro.ipynb diff --git a/VAPs/precipbe/precipbe_intro.ipynb b/VAPs/precipbe/precipbe_intro.ipynb new file mode 100644 index 00000000..92bf57af --- /dev/null +++ b/VAPs/precipbe/precipbe_intro.ipynb @@ -0,0 +1,9221 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "c4481c2c-d123-43ee-a810-5078b3861d39", + "metadata": {}, + "source": [ + "\"ARM" + ] + }, + { + "cell_type": "markdown", + "id": "866cfcb4-e973-4a63-849c-5494ea2daa92", + "metadata": {}, + "source": [ + "# The Precipitation Best-Estimate ([PrecipBE](https://www.arm.gov/capabilities/instruments/precipbe)) evaluation value-added product" + ] + }, + { + "cell_type": "markdown", + "id": "e231f47d-3ae0-4bf5-bfcd-70ed93fb2e50", + "metadata": {}, + "source": [ + "---" + ] + }, + { + "cell_type": "markdown", + "id": "5d42a115-2490-4878-8e6e-df0e3f75d9f4", + "metadata": {}, + "source": [ + "## Overview\n", + "This notebook demonstrates the use of the Precipitation Best-Estimate (PrecipBE) evaluation value-added product to visualize and analyze the temporal evolution of precipitation events and precipitation event statistics data from the HOU ([TRACER](https://www.arm.gov/research/campaigns/amf2021tracer)) deployment collected in April, 2022.\n", + "\n", + "1. Introduction to PrecipBE\n", + "1. How to access the data and load using Xarray\n", + "1. Processing and visualization" + ] + }, + { + "cell_type": "markdown", + "id": "d250388f-3a31-48c5-bde3-269c15008773", + "metadata": {}, + "source": [ + "---" + ] + }, + { + "cell_type": "markdown", + "id": "b33443a5-b086-45a3-b37c-88ad90a045de", + "metadata": {}, + "source": [ + "### Imports" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "8d1f1f5d-1233-435e-b32e-0c609d479715", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "import act\n", + "import os\n", + "import numpy as np\n", + "import xarray as xr\n", + "import matplotlib\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "from time import time\n", + "from datetime import datetime" + ] + }, + { + "cell_type": "markdown", + "id": "d62300ac-e6be-42bf-8460-5e0aa2ea0e9e", + "metadata": {}, + "source": [ + "## Overview of PrecipBE\n", + "\n", + "The precipitation best-estimate (precipBE) VAP serves as the go-to precipitation product for the ARM user community. The VAP includes two datastreams streamlining both process understanding and model evaluation studies using ARM precipitation data. The first datastream (precipbetseries) provides time series (evolving) precipitation data, whereas the second includes per-event statistics in an easy-to-use one-dimensional (tabular) format. The VAP processing is performed on a per precipitation-event basis, leveraging existing ARM measurement capabilities, depending on instrument availability (per deployment) while incorporating ARM DQR and data validity considerations. The precipbestats datastream also includes ancillary atmospheric-state data corresponding to each event, such as temperature, relative humidity, and a selected set of drop size distribution moments derived from [ARM disdrometer quantities VAPs](https://doi.org/10.2172/1808573) (where available).\n", + "\n", + "As an evaluation VAP, it is requested that data users communicate closely with the VAP points of contact, particularly regarding any issues." + ] + }, + { + "cell_type": "markdown", + "id": "0d35dbed-4d3f-4081-a058-f5f65105536e", + "metadata": {}, + "source": [ + "## How to Access PrecipBE Data from ARM" + ] + }, + { + "cell_type": "markdown", + "id": "f1c18e4c-edd1-4f2c-bc10-a722368be985", + "metadata": {}, + "source": [ + "### Use the ARM Live API to Download the Data, using ACT\n", + "\n", + "The Atmospheric Data Community Toolkit (ACT) has a helpful module to interface with the data server:\n", + "* [Download Data API](https://arm-doe.github.io/ACT/API/generated/act.discovery.html#module-act.discovery)" + ] + }, + { + "cell_type": "markdown", + "id": "68738ea1-33c0-4da6-bad1-be3c26366048", + "metadata": {}, + "source": [ + "### Setup our Download Query\n", + "Before downloading our data, we need to make sure we have an ARM Data Account, and ARM Live token. Both of these can be found using this link:\n", + "- [ARM Live Signup](https://adc.arm.gov/armlive/livedata/home)\n", + "\n", + "Once you sign up, you will see your token. Copy and replace that where we have `arm_username` and `arm_password` below.\n", + "\n", + "We will also need the two datastream names, which are `houprecipbetseriesM1.c1` (time series of precipitation events) and `houprecipbestatsM1.c1` (precipitation event statistics), representing:\n", + "- the site (HOU) and facility (M1)\n", + " - This information corresponds to the TRACER main site at Houston\n", + "- the product class (precipbe)\n", + " - This is the value-added product described in this notebook \n", + "- the product type (tseries and stats)\n", + " - Those are the two datasets derived from this product \n", + "- the data level (c1)\n", + " - This is the corrected, quality-controlled data " + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "4496d09c-e459-43a5-a13a-5cfa2a744aaf", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[DOWNLOADING] houprecipbetseriesM1.c1.20220426.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220429.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220417.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220414.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220419.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220423.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220405.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220407.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220420.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220421.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220408.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220406.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220422.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220415.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220411.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220416.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220430.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220413.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220412.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220403.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220425.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220418.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220401.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220424.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220427.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220409.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220404.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220428.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220410.000000.nc\n", + "[DOWNLOADING] houprecipbetseriesM1.c1.20220402.000000.nc\n", + "\n", + "If you use these data to prepare a publication, please cite:\n", + "\n", + "Silber, I. Precipitation Best Estimate (PRECIPBETSERIES), 2022-04-01 to\n", + "2022-04-30, ARM Mobile Facility (HOU), Houston, TX; AMF1 (main site for TRACER)\n", + "(M1). Atmospheric Radiation Measurement (ARM) User Facility.\n", + "https://doi.org/10.5439/2523642\n", + "\n", + "[DOWNLOADING] houprecipbestatsM1.c1.20220411.000000.nc\n", + "[DOWNLOADING] houprecipbestatsM1.c1.20220404.000000.nc\n", + "[DOWNLOADING] houprecipbestatsM1.c1.20220414.000000.nc\n", + "[DOWNLOADING] houprecipbestatsM1.c1.20220405.000000.nc\n", + "[DOWNLOADING] houprecipbestatsM1.c1.20220424.000000.nc\n", + "[DOWNLOADING] houprecipbestatsM1.c1.20220412.000000.nc\n", + "[DOWNLOADING] houprecipbestatsM1.c1.20220428.000000.nc\n", + "[DOWNLOADING] houprecipbestatsM1.c1.20220425.000000.nc\n", + "[DOWNLOADING] houprecipbestatsM1.c1.20220430.000000.nc\n", + "\n", + "If you use these data to prepare a publication, please cite:\n", + "\n", + "Silber, I. Precipitation Best Estimate (PRECIPBESTATS), 2022-04-01 to\n", + "2022-04-30, ARM Mobile Facility (HOU), Houston, TX; AMF1 (main site for TRACER)\n", + "(M1). Atmospheric Radiation Measurement (ARM) User Facility.\n", + "https://doi.org/10.5439/2523640\n", + "\n" + ] + } + ], + "source": [ + "arm_username = os.getenv(\"ARM_USERNAME\")\n", + "arm_password = os.getenv(\"ARM_PASSWORD\")\n", + "\n", + "tseries_datastream = \"houprecipbetseriesM1.c1\"\n", + "stats_datastream = \"houprecipbestatsM1.c1\"\n", + "\n", + "start_date = \"2022-04-01T00:00:00\"\n", + "end_date = \"2022-04-30T23:59:00\"\n", + "\n", + "tseries_files = act.discovery.download_arm_data(arm_username,\n", + " arm_password,\n", + " tseries_datastream,\n", + " start_date,\n", + " end_date)\n", + "\n", + "stats_files = act.discovery.download_arm_data(arm_username,\n", + " arm_password,\n", + " stats_datastream,\n", + " start_date,\n", + " end_date)" + ] + }, + { + "cell_type": "markdown", + "id": "017b8e47-a507-45c4-a8f9-c95d7dda6310", + "metadata": {}, + "source": [ + "As demonstrated in the output of the previous cell, PrecipBE time series datastreams include files for any given day, regardless of whether surface precipitation was measured. In contrast, the statistics datastreams include files only for days during which one or more precipitation events have started. For example, a TRACER precipitation event that began on 2022-04-25 and continued into 2022-04-26, which we will illustrate below, is recorded on the `houprecipbestatsM1.c1` data file for 2022-04-25. In this case, there is no file for 2022-04-26 since no precipitation events Began on that date." + ] + }, + { + "cell_type": "markdown", + "id": "69d96f67-6c98-402d-80f3-cd9f1527f755", + "metadata": {}, + "source": [ + "### Read and examine data files" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "92ec9374-66da-4e74-b43f-ce539d8c5177", + "metadata": {}, + "outputs": [], + "source": [ + "tseries_final = xr.open_mfdataset(tseries_files)\n", + "stats_final = xr.open_mfdataset(stats_files)" + ] + }, + { + "cell_type": "markdown", + "id": "335b6841-57d5-49bb-928e-3dff367010ea", + "metadata": {}, + "source": [ + "---" + ] + }, + { + "cell_type": "markdown", + "id": "2acad5a0-82ba-44c6-b2bd-d973a4b33cd6", + "metadata": {}, + "source": [ + "We can start by examining the time series dataset. This dataset provides the instrument-mean, min, max, and standard deviation of cumulative precipitation (per event) and 1-min precipitation rates, and is accompanied by various useful flags as well as the 1-min precipitation amount measured by all available instruments" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "a9e99c9b-dd6d-4c28-9241-8833631f6605", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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<xarray.Dataset> Size: 12MB\n",
+       "Dimensions:                                  (time: 43200, input_inst: 11)\n",
+       "Coordinates:\n",
+       "  * time                                     (time) datetime64[ns] 346kB 2022...\n",
+       "Dimensions without coordinates: input_inst\n",
+       "Data variables: (12/21)\n",
+       "    precipitation_rate                       (time) float64 346kB dask.array<chunksize=(512,), meta=np.ndarray>\n",
+       "    cumulative_precipitation                 (time) float64 346kB dask.array<chunksize=(480,), meta=np.ndarray>\n",
+       "    num_instruments                          (time) float32 173kB dask.array<chunksize=(1440,), meta=np.ndarray>\n",
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+       "    ...                                       ...\n",
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+       "    allowed_precip_free_period_min:                          30\n",
+       "    remove_outliers:                                         1\n",
+       "    event_aggregation_mode:                                  0\n",
+       "    ...                                                      ...\n",
+       "    datastream:                                              houprecipbetseri...\n",
+       "    data_level:                                              c1\n",
+       "    facility_id:                                             M1\n",
+       "    site_id:                                                 hou\n",
+       "    platform_id:                                             precipbetseries\n",
+       "    history:                                                 created by user ...
" + ], + "text/plain": [ + " Size: 12MB\n", + "Dimensions: (time: 43200, input_inst: 11)\n", + "Coordinates:\n", + " * time (time) datetime64[ns] 346kB 2022...\n", + "Dimensions without coordinates: input_inst\n", + "Data variables: (12/21)\n", + " precipitation_rate (time) float64 346kB dask.array\n", + " cumulative_precipitation (time) float64 346kB dask.array\n", + " num_instruments (time) float32 173kB dask.array\n", + " single_instrument_flag (time) float32 173kB dask.array\n", + " available_instruments (time) float64 346kB dask.array\n", + " instrument_invalid_samples_during_event (time) float64 346kB dask.array\n", + " ... ...\n", + " precipitation_amount_all_source (time, input_inst) float32 2MB dask.array\n", + " time_offset (time) datetime64[ns] 346kB dask.array\n", + " base_time (time) datetime64[ns] 346kB 2022...\n", + " lat (time) float64 346kB 29.67 ... 2...\n", + " lon (time) float64 346kB -95.06 ... ...\n", + " alt (time) float64 346kB 8.0 ... 8.0\n", + "Attributes: (12/31)\n", + " data_buffer_days: 7\n", + " event_total_minimum_mm: 0.1\n", + " event_total_minimum_mm_for_tbrg: 1.5\n", + " allowed_precip_free_period_min: 30\n", + " remove_outliers: 1\n", + " event_aggregation_mode: 0\n", + " ... ...\n", + " datastream: houprecipbetseri...\n", + " data_level: c1\n", + " facility_id: M1\n", + " site_id: hou\n", + " platform_id: precipbetseries\n", + " history: created by user ..." + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "tseries_final" + ] + }, + { + "cell_type": "markdown", + "id": "522f7c85-6c39-4b11-a70c-42962dfe19a9", + "metadata": {}, + "source": [ + "We can also examine the precipitation event statistics dataset we collected. Based on the `time` dimension, 11 precipitation events were observed in April, 2022. This dataset provides an extensive set of statistics characterizing each event (total amount, period, mean precipitation rate, and 1-min maximum precipitation rate). The dataset also includes a useful set of ancillary variables corresponding to the observed events, which will be demonstrated below." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "4f9c6f0a-6d58-4e27-9d10-1aa2d931d6be", + "metadata": { + "scrolled": true, + "tags": [] + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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<xarray.Dataset> Size: 9kB\n",
+       "Dimensions:                                     (time: 11)\n",
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+       "  * time                                        (time) datetime64[ns] 88B 202...\n",
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+       "    event_period                                (time) float64 88B dask.array<chunksize=(1,), meta=np.ndarray>\n",
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+       "    time_offset                                 (time) datetime64[ns] 88B dask.array<chunksize=(1,), meta=np.ndarray>\n",
+       "    base_time                                   (time) datetime64[ns] 88B 202...\n",
+       "    lat                                         (time) float64 88B 29.67 ... ...\n",
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+       "Attributes: (12/31)\n",
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+       "    allowed_precip_free_period_min:                          30\n",
+       "    remove_outliers:                                         1\n",
+       "    event_aggregation_mode:                                  0\n",
+       "    ...                                                      ...\n",
+       "    datastream:                                              houprecipbestats...\n",
+       "    data_level:                                              c1\n",
+       "    facility_id:                                             M1\n",
+       "    site_id:                                                 hou\n",
+       "    platform_id:                                             precipbestats\n",
+       "    history:                                                 created by user ...
" + ], + "text/plain": [ + " Size: 9kB\n", + "Dimensions: (time: 11)\n", + "Coordinates:\n", + " * time (time) datetime64[ns] 88B 202...\n", + "Data variables: (12/108)\n", + " event_period (time) float64 88B dask.array\n", + " event_start (time) float64 88B dask.array\n", + " event_end (time) float64 88B dask.array\n", + " event_mean_rate (time) float64 88B dask.array\n", + " event_max_rate (time) float64 88B dask.array\n", + " event_total (time) float64 88B dask.array\n", + " ... ...\n", + " total_droplet_concentration_std (time) float64 88B dask.array\n", + " time_offset (time) datetime64[ns] 88B dask.array\n", + " base_time (time) datetime64[ns] 88B 202...\n", + " lat (time) float64 88B 29.67 ... ...\n", + " lon (time) float64 88B -95.06 ......\n", + " alt (time) float64 88B 8.0 ... 8.0\n", + "Attributes: (12/31)\n", + " data_buffer_days: 7\n", + " event_total_minimum_mm: 0.1\n", + " event_total_minimum_mm_for_tbrg: 1.5\n", + " allowed_precip_free_period_min: 30\n", + " remove_outliers: 1\n", + " event_aggregation_mode: 0\n", + " ... ...\n", + " datastream: houprecipbestats...\n", + " data_level: c1\n", + " facility_id: M1\n", + " site_id: hou\n", + " platform_id: precipbestats\n", + " history: created by user ..." + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "stats_final" + ] + }, + { + "cell_type": "markdown", + "id": "1899a60b-9d33-493a-ba60-58fa7cb04519", + "metadata": {}, + "source": [ + "### Analysis and visualization" + ] + }, + { + "cell_type": "markdown", + "id": "2c5cc17b-186b-495e-89d8-1868e1c04dc3", + "metadata": {}, + "source": [ + "---" + ] + }, + { + "cell_type": "markdown", + "id": "31195126-0b21-41ef-a303-b67e270c6e99", + "metadata": {}, + "source": [ + "We can examine (and export) joint distributions of different statistics (here we utilize seaborn, so we need to convert the statistics dataset to a pandas DataFrame). Note that we also plot two ancillary variables,`temp_mean` and `total_droplet_concentration_mean`, which are the event-mean temperature and event-mean estimated droplet number concentration calculated using [MET](https://www.arm.gov/capabilities/instruments/met) and [VDISQUANTS](https://www.arm.gov/data/science-data-products/vaps/vdisquants) data, respectively." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "864281b7-3e63-400b-86ed-6a0eba9ee7be", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plots_path = './'\n", + "stats_df = stats_final.to_pandas() # convert to a dataframe\n", + "stats_df[\"event_no\"] = np.arange(1, len(stats_df) + 1) # add an event index for easy identification\n", + "vars_to_plot = [\"event_total\",\n", + " \"event_period\",\n", + " \"event_max_rate\",\n", + " \"event_mean_rate\",\n", + " \"total_droplet_concentration_mean\",\n", + " \"temp_mean\"\n", + " ] # variables to plot\n", + "\n", + "Jhist = sns.pairplot(stats_df, vars=vars_to_plot, kind=\"scatter\", corner=True, diag_kind=None, hue=\"event_no\", palette=\"tab20\")\n", + "Jhist.fig.savefig(plots_path + \"precipbe_joint_hist.png\")" + ] + }, + { + "cell_type": "markdown", + "id": "c6a00849-a0d0-45ba-94e0-feb56c543c23", + "metadata": {}, + "source": [ + "Say we are interested in the most significant event in this dataset, which we'll define, for simplicity, as the event with the highest total precipitation. Based on the plot above, we can see that event #9 (indicated by the purple marker) stands out. In comparison to the other events observed in April 2022, this event was also the longest, with the highest precipitation rates and estimated droplet number concentrations, and was characterized by the lowest temperatures.\n", + "We want to examine the event's temporal evolution (e.g., did rain fall at a relatively uniform rate or did it occur in short downpour instances?). We begin by finding that event (based on the fact that it had the highest total amount) and its onset and end times." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "c747efba-6589-49c2-a582-6c9b300af398", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Event began at 2022-04-25T20:36:01.000000and ended at 2022-04-26T01:32:44.000000\n" + ] + } + ], + "source": [ + "event_df = stats_df.loc[stats_df[\"event_total\"].idxmax(), :]\n", + "print(f'Event began at {(event_df[\"event_start\"].astype(\"timedelta64[s]\") + np.datetime64(event_df[\"base_time\"]))}'\n", + " f'and ended at {(event_df[\"event_end\"].astype(\"timedelta64[s]\") + np.datetime64(event_df[\"base_time\"]))}')" + ] + }, + { + "cell_type": "markdown", + "id": "2adcdd76-bf6f-4e58-9766-76e07593e1a2", + "metadata": {}, + "source": [ + "We can get part of the answer to the question raised above concerning precipitation rate uniformity even before we plot the time series by evaluating the event's precipitation rate standard deviation." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "bc7509d1-c82f-4824-a836-2383453629b5", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The event's precipitation rate standard deviation is 11.05 mm/hr, ~77% of the mean rate\n" + ] + } + ], + "source": [ + "print(f\"The event's precipitation rate standard deviation is {event_df['event_rate_std']:.2f} {stats_final['event_rate_std'].attrs['units']}, \"\n", + " f\"~{event_df['event_mean_rate'] / event_df['event_rate_std'] * 100:.0f}% of the mean rate\")" + ] + }, + { + "cell_type": "markdown", + "id": "7b35cda3-53aa-4c77-a0e4-0fc30fe0f1b9", + "metadata": {}, + "source": [ + "With this information we suspect that the event was quite variable and non-uniform. To conclude this brief demo. let's generate two plots depicting the event's evolution from the cumulative and 1-min precipitate rate perspectives." + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "id": "7315c45d-78f2-432a-bd29-c8c450118aee", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_stime = np.datetime64('2022-04-25T20:00:00')\n", + "plot_etime = np.datetime64('2022-04-26T02:00:00')\n", + "tseries_set = tseries_final.sel(time=slice(plot_stime, plot_etime))\n", + "for var in [\"precipitation_rate\", \"cumulative_precipitation\"]:\n", + " fig, ax = plt.subplots(figsize=(10, 4)) # for poster\n", + " ax.fill_between(tseries_set[\"time\"].values,\n", + " tseries_set[f\"{var}\"].values - tseries_set[f\"{var}_std\"],\n", + " tseries_set[f\"{var}\"].values + tseries_set[f\"{var}_std\"],\n", + " facecolor='k',\n", + " alpha=0.5,\n", + " label=r\"mean $\\pm 1\\sigma$\")\n", + " tseries_set[f\"{var}\"].plot(c='k', label='mean')\n", + " tseries_set[f\"{var}_min\"].plot(c='OrangeRed', linestyle='--', label='min')\n", + " tseries_set[f\"{var}_max\"].plot(c='DarkOrange', linestyle=':', label='max')\n", + " ax.grid('all')\n", + " ax.legend()\n", + " ax.set_ylabel(f'{var.replace(\"_\", \" \")} [{tseries_set[var].attrs[\"units\"]}]')\n", + " ax.set_xlabel(r\"UTC time\")\n", + " fig.savefig(f\"apr25_event_{var}.png\", dpi=150)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python [conda env:.conda-ARM_suite]", + "language": "python", + "name": "conda-env-.conda-ARM_suite-py" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.8" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 9d5095b089a94228d32f32daf7ac4f39ccdf57e9 Mon Sep 17 00:00:00 2001 From: isilber Date: Thu, 10 Jul 2025 16:35:54 +0000 Subject: [PATCH 2/2] MNT: remove redundant imports --- VAPs/precipbe/precipbe_intro.ipynb | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) diff --git a/VAPs/precipbe/precipbe_intro.ipynb b/VAPs/precipbe/precipbe_intro.ipynb index 92bf57af..a010a34f 100644 --- a/VAPs/precipbe/precipbe_intro.ipynb +++ b/VAPs/precipbe/precipbe_intro.ipynb @@ -66,11 +66,8 @@ "import os\n", "import numpy as np\n", "import xarray as xr\n", - "import matplotlib\n", "import matplotlib.pyplot as plt\n", - "import seaborn as sns\n", - "from time import time\n", - "from datetime import datetime" + "import seaborn as sns" ] }, {