ice_sheet_gmb-2.ipynb

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   "cell_type": "markdown",
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   "source": [
    "## Use case: Using Greenland and Antarctic ice sheet mass change data as indicators for global climatic and water cycle changes in the context of the current global warming."
   ]
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   "source": [
    "## Quality assessment question: \"Is the dataset sufficiently consistent in terms of spatio-temporal completeness and resolution to derive multi-year trends in ice sheet mass changes and their corresponding contribution to global sea level rise?\""
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   "cell_type": "markdown",
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    "Ice sheets are a major contributor to current (and potentially future) global sea-level rise and can serve as clear indicators of ongoing climatic changes. Their changes furthermore play a key role in affecting (polar as well as global) ecosystems and several (feedback) mechanisms within the atmosphere, ocean and cryosphere. A proper assessment of ice sheet mass changes due to warming climatic conditions therefore plays a crucial role in dealing with these issues. In that regard, the 'Gravimetric mass balance data for the Antarctic and Greenland ice sheets from 2003 to 2022 derived from satellite observations' dataset provides key information with respect to ice sheet mass change data for both the Greenland and Antarctic ice sheets. The dataset on the Climate Data Store (CDS) is based on satellite gravimetry, which enable mass changes to be measured regularly and consistently over the entire ice sheets. Remote sensing devices, such as used by the GRACE and GRACE-FO missions, are namely able to inspect directly and repeatedly large areas of ice. More particularly, the GRACE(-FO) mission is able to detect changes within the Earth’s gravitational field (resembling a redistribution of mass), and further processing of these data transforms this raw information into mass balance and mass change data of ice above buyoancy (Forsberg et al., 2017; Groh et al., 2019). Remote sensing techniques that use satellite data are therefore considered the only feasible manner to derive accurate mass change data of the remote ice sheets on a regular basis. This notebook investigates how well the resulting ice sheet mass change data can be used to monitor global climatic and water cycle changes. More specifically, the notebook investigates whether the dataset is of sufficient maturity and quality in terms of its spatio-temporal completeness and resolution to derive multi-year trends in ice sheet mass changes and their corresponding contribution to global sea level rise."
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   "cell_type": "markdown",
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   "source": [
    "## 📌 Quality assessment statement"
   ]
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    "- Mass change detection by GRACE(-FO) is a useful tool to quantify the total ice mass change of the Greenland and Antarctic Ice Sheet but, however, it also has its limitations of which the user should take note before using the product. What GRACE(-FO) actually detects are patterns of mass redistribution, indicating that a material should be redistributed (e.g. by liquid discharge) in order for GRACE(-FO) to be able to detect the mass changes over certain locations. In that sense, an amount of melted ice being replaced by its mass-equivalent amount of meltwater at the same location would result in zero mass change. Only grounded ice mass changes above sea level are considered in the dataset, mass changes of floating ice and ice grounded below sea level (ice below buyoancy) are not considered (which is, however, relatively limited for the GrIS but can be significant for the AIS). GRACE(-FO) data are therefore considered to be the sum of mass changes driven by changing rates of solid ice discharge (i.e. ice dynamics) and mass changes driven by changing rates of runoff and accumulation (basal, internal and surface conditions) over grounded ice above sea level.\n",
    "- A large problem with the dataset is that no pixel-by-pixel mass change and error products are included for the ice sheets. Instead, only time series data of cumulative mass changes for various basins and the complete ice sheet are available from the data files. A spatial resolution at the basin-level is, however, clearly too coarse with respect to GCOS requirements (GCOS, 2022). Another issue with the data is the occurrence of (occasionally very) high error values. Data gaps are also present (e.g. during the transition period between GRACE and GRACE-FO in 2017-2018 CE). These are not filled up and not flagged, users need to identify them themselves.\n",
    "- Concerning the specific use case and user question, it can be stated that GRACE(-FO) data, with its ice sheet-wide coverage and monthly temporal resolution, effectively captures long-term trends (> 20 years) in ice sheet mass changes, serving as a reliable indicator of global climate change and sea level contributions. The dataset is suitable for assessing ice sheet-wide and basin-scale mass changes due to its comprehensive temporal and spatial coverage, despite a significant gap between GRACE and GRACE-FO in 2017-2018. However, users should be aware of its limitations, such as coarse spatial resolution and relatively high uncertainties (due to corrections for e.g. signal leakge or glacial isostatic adjustment), which require careful handling. Overall, GRACE(-FO) provides valuable data on ice mass changes, making it a crucial tool for understanding and quantifying global climate change and water cycle dynamics."
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   "cell_type": "markdown",
   "id": "2530840b-48c9-47a9-b8ec-48cc81ffd7fb",
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   "source": [
    "## ❓ Methodology"
   ]
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   "cell_type": "markdown",
   "id": "c7b2ee91-b41f-4336-ae69-dd6bdc966885",
   "metadata": {},
   "source": [
    "#### Short description"
   ]
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   "cell_type": "markdown",
   "id": "9a9be4c9-013d-44a8-a14f-832734350c8b",
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   "source": [
    "The mass balance of an ice sheet is the difference between mass gained (from snow accumulation) and mass lost (by runoff or ice discharge through the grounding line), which is the same as the net mass change of the ice sheet. Remote sensing techniques, such as the use of satellites, are an important feature to derive and study the mass changes of the ice sheets. The 'Gravimetric mass balance data for the Antarctic and Greenland ice sheets from 2003 to 2020 derived from satellite observations' dataset provides monthly gravimetric mass balance (GMB) values and their uncertainty for the Greenland (GrIS) and Antarctic Ice Sheet (AIS). The data represent a time series of the cumulative mass changes of the grounded ice of the ice sheets and their basins that are derived using satellite gravimetry data from the GRACE(-FO) missions. Data are available for the whole ice sheet as well as at the basin level, but no gridded data are provided. Data are available since 2002 with units in Gt (Gigatonnes). For a more detailed description of the data acquisition and processing methods, we refer to the documentation on the CDS and the ECMWF Confluence Wiki."
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   "cell_type": "markdown",
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   "source": [
    "#### Structure and (sub)sections"
   ]
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   "cell_type": "markdown",
   "id": "ff38d788-bb40-4ea2-824a-03a91b139f90",
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   "source": [
    "In this notebook, the applicability of ice sheet mass change data to be used for global climate change and water cycle change monitoring will be assessed. We will check whether the data for are of sufficient adequacy in terms of its accuracy and its spatio-temporal completeness and resolution to be used for this purpose. This will be realized by analyzing the spatial and temporal characteristics of ice sheet mass change data, by assessing the spatial and temporal resolution and coverage of the dataset, by discussing other potential limitations and error sources of the dataset, and by evaluating the implications for the usage of the data in terms of the specific use case and question (i.e. monitoring global climate and global water cycle changes). The structure is as follows:\n",
    "\n",
    "- **Data preparation and processing**: This section loads packages, defines requests for download from the CDS, downloads the actual data and inspects the data to reveal its structure. Also the functions that are used in this notebook are defined in this section.\n",
    "- **Quantifying Greenland and Antarctic Ice Sheet mass changes over time**: This section derives and discusses cumulative ice sheet mass changes for Greenland and Antarctica since 2002 from GRACE-(FO) and expresses it as a time series for the ice sheet-wide spatial scale.\n",
    "- **Analysis of spatio-temporal resolution and coverage of the GRACE(-FO) mass change estimates**: This section further discusses the temporal and spatial coverage of the data in the ice sheet mass change product, and quantifies the amount of data gaps present.\n",
    "- **Ice sheet mass changes (linear and quadratic) trends and sea level contribution over time**: Here, we calculate the linear and quadratic trend of the ice sheet-wide ice mass change time series. We also convert the cumulative mass changes into global sea level changes.\n",
    "- **Implications for use of GRACE(-FO) mass change data as global climate change and sea level change indicators**: The final section uses all information derived above to assess the suitability of the ice sheet mass change dataset (with respect to its spatial/temporal coverage and resolution) to use the product as indicators for global climatic and water cycle changes in the context of the current global warming."
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   "cell_type": "markdown",
   "id": "c228859f-400e-4e02-82c0-2788585bdfa7",
   "metadata": {},
   "source": [
    "## 📋 Analysis and results"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "75964289-16da-4d86-b40d-e6dfa7427840",
   "metadata": {},
   "source": [
    "### ⏬ Data preparation and processing"
   ]
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   "cell_type": "markdown",
   "id": "57e95fe7-a070-4bfd-a138-bc819a9297cf",
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   "source": [
    "First we load the packages:"
   ]
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   "cell_type": "code",
   "execution_count": 26,
   "id": "b448380f-32fe-49cd-80a6-6b73e084f3fa",
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   "source": [
    "import fsspec\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.colors as mcolors\n",
    "import matplotlib.ticker as mticker\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "from scipy.stats import linregress\n",
    "from matplotlib.gridspec import GridSpec\n",
    "import re\n",
    "from math import ceil\n",
    "import scipy.stats\n",
    "import pandas as pd\n",
    "import calendar\n",
    "import os\n",
    "os.environ[\"CDSAPI_RC\"] = os.path.expanduser(\"~/verhaegen_yoni/.cdsapirc\")\n",
    "from c3s_eqc_automatic_quality_control import download\n",
    "\n",
    "plt.style.use(\"seaborn-v0_8-notebook\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "947a5384-9f42-42d8-967c-8418e5a588cd",
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   "source": [
    "Then we define the parameters, i.e. for which ice sheet (or which basins of these ice sheets) we want the mass change data to be extracted:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "8fd721fc-b1c4-47f4-b614-4198e48f6c7f",
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   "source": [
    "variables = [\"GrIS_total\", \"AntIS_total\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42bc4137-78a1-4063-997c-2fb7be5e2ab0",
   "metadata": {},
   "source": [
    "Then we define requests for download from the CDS and download and transform the glacier mass change data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "65e9950a-773e-4e37-8c19-0fd53dc5c89a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1/1 [00:00<00:00,  3.26it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading done.\n"
     ]
    }
   ],
   "source": [
    "collection_id = \"satellite-ice-sheet-mass-balance\"\n",
    "request = {\n",
    "    \"variable\": \"all\",\n",
    "    \"format\": \"zip\",\n",
    "}\n",
    "ds = download.download_and_transform(collection_id, request)\n",
    "ds = ds[variables].compute()\n",
    "ds = xr.combine_by_coords([ds])\n",
    "print(\"Downloading done.\")"
   ]
  },
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   "cell_type": "markdown",
   "id": "5fbbef79-9819-4dbd-9dba-b9d021e5ebdd",
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   "source": [
    "Let us inspect the data:"
   ]
  },
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   "cell_type": "code",
   "execution_count": 46,
   "id": "c9103e4b-a67f-46e8-b399-473e529240e0",
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       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
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       ".xr-var-data,\n",
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       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
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       "}\n",
       "\n",
       ".xr-var-data > table {\n",
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       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
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       "\n",
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       "  grid-template-columns: 125px auto;\n",
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       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
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       "  width: auto;\n",
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
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       "\n",
       ".xr-attrs dd {\n",
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       "  white-space: pre-wrap;\n",
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       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 3kB\n",
       "Dimensions:      (time: 216)\n",
       "Coordinates:\n",
       "  * time         (time) datetime64[ns] 2kB 2002-04-16T20:23:54.375000 ... 202...\n",
       "Data variables:\n",
       "    GrIS_total   (time) float32 864B 1.057e+03 1.123e+03 ... -3.762e+03\n",
       "    AntIS_total  (time) float32 864B 345.6 488.9 467.3 ... -910.0 -843.2 nan\n",
       "Attributes:\n",
       "    Title:                GMB for Greenland and Antarctica ice sheets from th...\n",
       "    institution:          DTU Space - Geodesy and Earth Observations\n",
       "    reference:            Baratta et al. (2016), Groh and Horwart (2016)\n",
       "    file_creation_date:   Tue May 16 09:49:32 2023\n",
       "    region:               Greenland and Antarctica\n",
       "    missions_used:        GRACE and and GRACE-FO\n",
       "    time_coverage_start:  Apr-2002\n",
       "    time_coverage_end:    Dec-2022\n",
       "    Tracking_id:          ab2360a4-82d5-42f3-babb-90ce976a8a8e\n",
       "    netCDF_version:       NETCDF4\n",
       "    product_version:      4.0\n",
       "    Summary:              This data set is prepared for the C3S project, and ...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-2ac96b89-0752-4ef2-b2f6-6c670b908aeb' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2ac96b89-0752-4ef2-b2f6-6c670b908aeb' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 216</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-13bc6f1c-901e-45b9-8ae6-6afa0e21252e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-13bc6f1c-901e-45b9-8ae6-6afa0e21252e' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2002-04-16T20:23:54.375000 ... 2...</div><input id='attrs-a0c97250-1225-4e13-b7ec-a6e1fbe1da89' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a0c97250-1225-4e13-b7ec-a6e1fbe1da89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89056acd-f8f8-4ccb-b61d-157ebf3490e5' class='xr-var-data-in' type='checkbox'><label for='data-89056acd-f8f8-4ccb-b61d-157ebf3490e5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2002-04-16T20:23:54.375000000&#x27;, &#x27;2002-05-12T09:36:05.625000000&#x27;,\n",
       "       &#x27;2002-08-15T07:12:11.250000000&#x27;, ..., &#x27;2022-10-16T08:24:22.500000000&#x27;,\n",
       "       &#x27;2022-11-18T04:48:45.000000000&#x27;, &#x27;2022-12-17T09:35:37.500000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-85362969-a5a6-44ad-9418-c83808338fa3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-85362969-a5a6-44ad-9418-c83808338fa3' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>GrIS_total</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.057e+03 1.123e+03 ... -3.762e+03</div><input id='attrs-92c31c3a-712f-48b9-a9a9-1d6381267651' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-92c31c3a-712f-48b9-a9a9-1d6381267651' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a90be6ea-2622-482d-acdc-0616379a639e' class='xr-var-data-in' type='checkbox'><label for='data-a90be6ea-2622-482d-acdc-0616379a639e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Greenland_ice_sheet_total_GMB</dd><dt><span>units :</span></dt><dd>Gt</dd></dl></div><div class='xr-var-data'><pre>array([ 1057.3158  ,  1122.5491  ,   801.4892  ,   685.4882  ,\n",
       "         834.5923  ,   837.24176 ,   901.733   ,  1152.2305  ,\n",
       "         950.7364  ,  1018.03424 ,  1057.121   ,  1052.3649  ,\n",
       "         863.40375 ,   659.544   ,   668.2711  ,   754.7539  ,\n",
       "         785.51776 ,   716.28973 ,   731.79626 ,   737.9634  ,\n",
       "         769.46216 ,   847.06586 ,   802.278   ,   822.9911  ,\n",
       "         651.4231  ,   523.5984  ,   482.68774 ,   416.10977 ,\n",
       "         538.17334 ,   548.3054  ,   475.78656 ,   532.18884 ,\n",
       "         605.61334 ,   620.64886 ,   654.5307  ,   611.3686  ,\n",
       "         475.77783 ,   295.96472 ,   184.42964 ,   201.96304 ,\n",
       "         205.77531 ,   311.1006  ,   213.75298 ,   246.94975 ,\n",
       "         372.09155 ,   312.12695 ,   381.0937  ,   333.07675 ,\n",
       "         273.12085 ,   133.90897 ,     7.996562,    28.998074,\n",
       "         135.96179 ,    99.998055,   120.16927 ,   196.41817 ,\n",
       "         144.95966 ,   155.674   ,   190.05008 ,   166.28227 ,\n",
       "         -31.717527,  -188.88943 ,  -227.03    ,  -247.80621 ,\n",
       "        -204.38718 ,  -242.23709 ,  -191.14406 ,  -103.96201 ,\n",
       "        -111.620316,   -16.052423,  -106.66183 ,  -144.60994 ,\n",
       "        -295.8416  ,  -500.1301  ,  -482.59558 ,  -522.9934  ,\n",
       "        -405.99142 ,  -428.33243 ,  -352.0839  ,  -252.57489 ,\n",
       "...\n",
       "       -2312.5566  , -2114.5317  , -2194.3533  , -2144.8281  ,\n",
       "       -2165.575   , -2380.574   , -2417.9792  , -2507.9614  ,\n",
       "       -2465.2253  , -2424.02    , -2391.769   , -2374.249   ,\n",
       "       -2310.9685  , -2362.6372  , -2573.4458  , -2757.4097  ,\n",
       "       -2646.3303  , -2762.8127  , -2558.8555  , -2632.2385  ,\n",
       "       -2484.3174  , -2577.7766  , -2611.1167  , -2632.2766  ,\n",
       "       -2674.6047  , -2813.3591  , -2720.4456  , -2739.9731  ,\n",
       "       -2759.4563  , -2830.864   , -2844.574   , -2779.3806  ,\n",
       "       -2805.212   , -2784.0647  , -3031.3284  , -3220.9775  ,\n",
       "       -3291.8484  , -3343.7922  , -3278.5583  , -3262.037   ,\n",
       "       -3336.6245  , -3294.164   , -3374.9788  , -3383.2776  ,\n",
       "       -3318.7397  , -3321.8525  , -3461.7854  , -3640.0034  ,\n",
       "       -3585.19    , -3498.5818  , -3430.7725  , -3521.548   ,\n",
       "       -3426.9727  , -3425.8147  , -3512.1895  , -3426.186   ,\n",
       "       -3443.969   , -3559.779   , -3632.3472  , -3703.4885  ,\n",
       "       -3656.4353  , -3900.2397  , -3651.7231  , -3763.1694  ,\n",
       "       -3677.0059  , -3711.8901  , -3630.6487  , -3564.005   ,\n",
       "       -3812.131   , -3735.7803  , -3712.164   , -3902.6807  ,\n",
       "       -3881.0034  , -4028.8796  , -3751.5413  , -3761.7322  ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>AntIS_total</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>345.6 488.9 467.3 ... -843.2 nan</div><input id='attrs-84e55670-afb2-4b8f-aa44-213b71f21636' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-84e55670-afb2-4b8f-aa44-213b71f21636' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-84d04da0-dcfa-4d2d-90bb-b5f265f3c32a' class='xr-var-data-in' type='checkbox'><label for='data-84d04da0-dcfa-4d2d-90bb-b5f265f3c32a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Antarctic_ice_sheet_total_GMB</dd><dt><span>units :</span></dt><dd>Gt</dd></dl></div><div class='xr-var-data'><pre>array([  345.65    ,   488.89413 ,   467.2695  ,   551.82904 ,\n",
       "         552.61    ,   381.20416 ,   429.01718 ,   332.9419  ,\n",
       "         272.30963 ,   320.22348 ,   463.44757 ,   482.62238 ,\n",
       "         485.122   ,   532.002   ,   441.72095 ,   507.54    ,\n",
       "         428.81583 ,   236.0918  ,   183.43398 ,    54.208614,\n",
       "         279.33795 ,   137.95    ,   363.48843 ,   365.24323 ,\n",
       "         333.86227 ,   451.9029  ,   350.59    ,   520.19    ,\n",
       "         388.3276  ,   298.68    ,   233.38245 ,   110.638145,\n",
       "         191.39603 ,   347.29178 ,   347.87274 ,   362.7947  ,\n",
       "         388.11905 ,   387.2814  ,   434.92    ,   518.12    ,\n",
       "         608.9     ,   487.36612 ,   352.86258 ,   227.27112 ,\n",
       "         361.64517 ,   413.04642 ,   608.1512  ,   501.95746 ,\n",
       "         512.29047 ,   571.5093  ,   578.65045 ,   543.86    ,\n",
       "         441.64667 ,   403.6347  ,   185.89352 ,   149.445   ,\n",
       "         196.8353  ,   307.05072 ,   403.86975 ,   383.91818 ,\n",
       "         394.83682 ,   395.90976 ,   429.76953 ,   379.96    ,\n",
       "         255.69167 ,   106.89082 ,   -27.753881,    28.444927,\n",
       "         -41.73518 ,   116.34    ,   236.64494 ,   247.27325 ,\n",
       "          80.69325 ,   122.26687 ,   258.5075  ,   197.5075  ,\n",
       "         248.45143 ,   164.48    ,    11.892683,    92.41141 ,\n",
       "...\n",
       "        -744.1213  ,  -825.79626 ,  -749.69653 ,  -762.05    ,\n",
       "        -660.72327 ,  -636.6403  ,  -675.6858  ,  -613.3082  ,\n",
       "        -813.9148  ,  -874.4521  ,  -768.83    ,  -770.23926 ,\n",
       "        -909.03076 ,  -597.52814 ,  -458.07327 ,  -572.3539  ,\n",
       "        -775.7716  ,  -730.32837 ,  -862.1497  , -1010.75    ,\n",
       "        -360.95    ,  -603.0776  ,  -438.44482 ,  -755.38    ,\n",
       "        -724.18    ,  -949.3237  ,  -907.3325  , -1003.4882  ,\n",
       "       -1061.8412  , -1138.5074  ,  -851.8607  ,  -730.7807  ,\n",
       "        -787.0664  ,  -882.7875  ,  -779.19244 ,  -805.2913  ,\n",
       "        -640.24286 ,  -903.3     , -1027.2333  , -1094.4424  ,\n",
       "       -1351.5718  , -1405.8123  , -1203.9783  , -1155.4     ,\n",
       "       -1115.3807  , -1069.6754  ,  -815.6849  ,  -682.07263 ,\n",
       "        -921.88763 , -1111.2971  , -1170.3096  , -1284.5     ,\n",
       "       -1596.1097  , -1304.226   , -1318.1195  ,  -998.0129  ,\n",
       "        -976.4891  , -1069.618   , -1188.3848  , -1247.773   ,\n",
       "       -1201.8143  , -1120.1     , -1347.075   , -1305.2341  ,\n",
       "       -1164.8105  , -1233.8112  , -1181.5369  ,  -756.38214 ,\n",
       "        -596.9726  ,  -836.9681  ,  -978.89825 ,  -966.4277  ,\n",
       "        -767.381   ,  -910.      ,  -843.1567  ,          nan],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-68a8d4c6-d750-4d1f-b69e-eda53118f857' class='xr-section-summary-in' type='checkbox'  ><label for='section-68a8d4c6-d750-4d1f-b69e-eda53118f857' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0a8d63b9-77e7-495c-8b19-84ca7471b3f7' class='xr-index-data-in' type='checkbox'/><label for='index-0a8d63b9-77e7-495c-8b19-84ca7471b3f7' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2002-04-16 20:23:54.375000&#x27;, &#x27;2002-05-12 09:36:05.625000&#x27;,\n",
       "               &#x27;2002-08-15 07:12:11.250000&#x27;, &#x27;2002-09-17 03:36:05.625000&#x27;,\n",
       "               &#x27;2002-10-16 08:23:54.375000&#x27;, &#x27;2002-11-18 04:47:48.750000&#x27;,\n",
       "               &#x27;2002-12-17 09:36:05.625000&#x27;, &#x27;2003-01-15 14:23:54.375000&#x27;,\n",
       "               &#x27;2003-02-13 19:12:11.250000&#x27;, &#x27;2003-03-18 15:36:05.625000&#x27;,\n",
       "               ...\n",
       "               &#x27;2022-03-18 15:35:37.500000&#x27;, &#x27;2022-04-16 20:24:22.500000&#x27;,\n",
       "                      &#x27;2022-05-16 01:11:15&#x27;, &#x27;2022-06-17 21:35:37.500000&#x27;,\n",
       "               &#x27;2022-07-17 02:24:22.500000&#x27;,        &#x27;2022-08-15 07:11:15&#x27;,\n",
       "               &#x27;2022-09-17 03:35:37.500000&#x27;, &#x27;2022-10-16 08:24:22.500000&#x27;,\n",
       "                      &#x27;2022-11-18 04:48:45&#x27;, &#x27;2022-12-17 09:35:37.500000&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=216, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-045c717e-60bd-488e-8f99-63b5c03542cb' class='xr-section-summary-in' type='checkbox'  ><label for='section-045c717e-60bd-488e-8f99-63b5c03542cb' class='xr-section-summary' >Attributes: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Title :</span></dt><dd>GMB for Greenland and Antarctica ice sheets from the GRACE missions</dd><dt><span>institution :</span></dt><dd>DTU Space - Geodesy and Earth Observations</dd><dt><span>reference :</span></dt><dd>Baratta et al. (2016), Groh and Horwart (2016)</dd><dt><span>file_creation_date :</span></dt><dd>Tue May 16 09:49:32 2023</dd><dt><span>region :</span></dt><dd>Greenland and Antarctica</dd><dt><span>missions_used :</span></dt><dd>GRACE and and GRACE-FO</dd><dt><span>time_coverage_start :</span></dt><dd>Apr-2002</dd><dt><span>time_coverage_end :</span></dt><dd>Dec-2022</dd><dt><span>Tracking_id :</span></dt><dd>ab2360a4-82d5-42f3-babb-90ce976a8a8e</dd><dt><span>netCDF_version :</span></dt><dd>NETCDF4</dd><dt><span>product_version :</span></dt><dd>4.0</dd><dt><span>Summary :</span></dt><dd>This data set is prepared for the C3S project, and is brokered from the CCI+ projects of Antarctica and Greenland ice sheets</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 3kB\n",
       "Dimensions:      (time: 216)\n",
       "Coordinates:\n",
       "  * time         (time) datetime64[ns] 2kB 2002-04-16T20:23:54.375000 ... 202...\n",
       "Data variables:\n",
       "    GrIS_total   (time) float32 864B 1.057e+03 1.123e+03 ... -3.762e+03\n",
       "    AntIS_total  (time) float32 864B 345.6 488.9 467.3 ... -910.0 -843.2 nan\n",
       "Attributes:\n",
       "    Title:                GMB for Greenland and Antarctica ice sheets from th...\n",
       "    institution:          DTU Space - Geodesy and Earth Observations\n",
       "    reference:            Baratta et al. (2016), Groh and Horwart (2016)\n",
       "    file_creation_date:   Tue May 16 09:49:32 2023\n",
       "    region:               Greenland and Antarctica\n",
       "    missions_used:        GRACE and and GRACE-FO\n",
       "    time_coverage_start:  Apr-2002\n",
       "    time_coverage_end:    Dec-2022\n",
       "    Tracking_id:          ab2360a4-82d5-42f3-babb-90ce976a8a8e\n",
       "    netCDF_version:       NETCDF4\n",
       "    product_version:      4.0\n",
       "    Summary:              This data set is prepared for the C3S project, and ..."
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "291fcd47-f2b6-4b4a-9219-2e16398a23ad",
   "metadata": {},
   "source": [
    "It is a dataset that consists out of time series data, containing cumulative values of the total ice sheet mass change of, in this case, the entire Greenland Ice Sheet (`GrIS_total`) and the entire Antarctic Ice Sheet (`AntIS_total`) since 2002. Mass changes are expressed in units of Gt and the time period between two measurements is variable. Note that no gridded data are given in this dataset, and hence no spatial resolution can be derived.\n",
    "\n",
    "Let us perform some data handling before getting started with the analysis. We also define a plotting function to visualize the time series:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "09677201-54e7-46f7-9d9f-44dcd68855a6",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_timeseries(ds):\n",
    "    # Define specific names for the first and second variables\n",
    "    variable_names = {\n",
    "        \"first_variable_name\": \"Cumulative mass change of the Greenland Ice Sheet from GRACE(-FO)\",\n",
    "        \"second_variable_name\": \"Cumulative mass change of the Antarctic Ice Sheet from GRACE(-FO)\"\n",
    "    }\n",
    "    \n",
    "    variables = list(ds.data_vars.values())\n",
    "    num_vars = len(variables)\n",
    "    \n",
    "    # Determine the number of columns needed based on the number of variables\n",
    "    num_cols = (num_vars + 1) // 2  # Integer division to ensure enough columns\n",
    "    \n",
    "    fig = plt.figure(figsize=(10 * num_cols, 8))\n",
    "    gs = GridSpec(2, num_cols, figure=fig)\n",
    "    \n",
    "    for i, var in enumerate(variables):\n",
    "        row = i % 2\n",
    "        col = i // 2\n",
    "        ax = fig.add_subplot(gs[row, col])\n",
    "        var.plot(ax=ax, color='k')\n",
    "        ax.set_title(f\"{var.attrs.get('region', '')}\")\n",
    "        ax.set_xlim(np.min(ds[\"time\"]), np.max(ds[\"time\"]))\n",
    "        ax.grid(color='#95a5a6', linestyle='-', alpha=0.25)\n",
    "\n",
    "    plt.tight_layout()\n",
    "    return fig, gs\n",
    "\n",
    "# Dataset processing\n",
    "variables_to_drop = [var for var in ds.data_vars if '_er' in var]\n",
    "ds = ds.drop_vars(variables_to_drop)\n",
    "\n",
    "year_to_ns = 1.0e9 * 60 * 60 * 24 * 365\n",
    "with xr.set_options(keep_attrs=True):\n",
    "    ds = ds - ds.isel(time=0)\n",
    "    \n",
    "# Set custom attributes for variables\n",
    "for i, (var, da) in enumerate(ds.data_vars.items()):\n",
    "    if i == 0:\n",
    "        da.attrs[\"region\"] = \"Cumulative mass change of the Greenland Ice Sheet from GRACE(-FO)\"\n",
    "    elif i == 1:\n",
    "        da.attrs[\"region\"] = \"Cumulative mass change of the Antarctic Ice Sheet from GRACE(-FO)\"\n",
    "    else:\n",
    "        da.attrs[\"region\"] = da.attrs[\"long_name\"].split(\"_\", 1)[0].title()\n",
    "    da.attrs[\"long_name\"] = \"Cumulative mass change\"\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84f18b97-9f50-442b-843f-f9ebb2bc98cc",
   "metadata": {},
   "source": [
    "With everything ready, let us now start with the analysis:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "82bfa3ea-b585-45d5-b688-766b41cbb087",
   "metadata": {},
   "source": [
    "### 📉 Quantifying Greenland and Antarctic Ice Sheet mass changes over time"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d592cdad-3017-41d9-8cd3-9aad77bf6743",
   "metadata": {},
   "source": [
    "We begin by plotting the Greenland and Antarctic Ice Sheet cumulative mass change $\\Delta M_{GRACE}$ between the begin and end period with the defined plotting function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "86eded0b-7b64-444c-804a-60d220367291",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, gs = plot_timeseries(ds)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "2d4aef7b-fa02-4ac7-87be-469b31c49b4e",
   "metadata": {},
   "source": [
    "The mass changes derived from GRACE(-FO) are measured in gigatonnes (Gt). One gigatonne (Gt) is a unit of mass, equivalent whether it is attributed to ice or water. For context, one Gt of water, with a density of 1000 kg/m$^3$, equals one cubic kilometer (km$^3$). In contrast, due to ice's density of 917 kg/m$^3$, one Gt of ice translates to 1.091 km$^3$. GRACE(-FO) data capture mass changes as a result of varying rates of solid ice discharge (due to ice dynamics) and shifts in runoff and accumulation rates (affected by basal, internal, and surface climatic conditions). Essentially, GRACE(-FO) detects patterns of mass redistribution, requiring material movement (such as liquid discharge) to identify gravity anomalies and mass changes at specific locations. Thus, melted ice replaced by an equivalent mass of meltwater at the same site results in zero net mass change. The dataset only includes changes in grounded ice mass above sea level, and hence excludes floating ice mass changes and ice grounded below sea level, which are relatively minimal for the Greenland Ice Sheet (GrIS) but can be significant for the Antarctic Ice Sheet (AIS). However, in the sense of climate change impact, the direct contribution of ice below buyoancy to global sea-level change is quasi zero.\n",
    "\n",
    "The provided graphs show the cumulative mass change of the Greenland Ice Sheet and the Antarctic Ice Sheet since 2002, as measured by GRACE(-FO) satellites. The Greenland Ice Sheet shows a clear and consistent decline in mass, having lost approximately 5000 gigatonnes (Gt) over the period. This steady loss, with brief periods of slowed decline, indicates a strong response to climatic factors such as rising temperatures, leading to increased liquid discharge (increased surface melt and runoff). In contrast, the Antarctic Ice Sheet also exhibits a downward trend, with a cumulative loss of around 2000 Gt by the end of the period. However, the Antarctic mass change graph displays more pronounced fluctuations, suggesting the influence of complex dynamics like variations in solid ice discharge rates and localized climatic conditions (e.g. increased precipitation). For Greenland, mass loss is dominated by surface melting and runoff, combined with the solid ice discharge through outlet glaciers. For Antarctica, mass loss primarily occurs through the discharge of ice past the grounding line (i.e. via iceberg calving and basal melting of ice shelves), with surface melting playing a minor role. Here, interactions between the ice sheet and the warming ocean, combined with dynamic responses within the ice sheet itself (e.g. an acceleration of outlet glaciers due to a reduced buttressing from the ice shelves), are central to understanding why Antarctica's mass is currently decreasing (Forsberg et al., 2017; Groh et al., 2019)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19d4666c-41df-4266-9537-5d10ffdbd5a0",
   "metadata": {},
   "source": [
    "### ✅ Analysis of spatio-temporal resolution and coverage of the GRACE(-FO) mass change estimates"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "95017fe7-162c-4aca-9e62-974c0a173a93",
   "metadata": {},
   "source": [
    "Now that we have visualized the temporal patterns of the mass changes, we can investigate the spatio-temporal resolution and extent of the GrIS and AIS mass changes. Let us begin by identifying temporal data gaps (coverage) and the temporal resolution in the time series:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "cd661072-bd9e-4b78-aa1e-d78ef0a15bcb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x550 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "time_gap_months = 12 * ds[\"time\"].diff(\"time\").astype(int) / year_to_ns\n",
    "\n",
    "# Create the plot\n",
    "fig, ax = plt.subplots()\n",
    "time_gap_months.plot(ax=ax, color='b')\n",
    "ax.set_ylabel(\"Time gap [month]\")\n",
    "ax.grid(color='#95a5a6', linestyle='-', alpha=0.25)\n",
    "ax.set_xlim(np.min(ds[\"time\"]), np.max(ds[\"time\"]))\n",
    "ax.set_title(\"Time gap since last valid GRACE(-FO) measurement\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e1d9bad-b2f6-4317-a3b8-40e434cfcf16",
   "metadata": {},
   "source": [
    "The plot displays the time gaps in the GRACE(-FO) data collection over time, which are the same for the GrIS and the AIS, highlighting periods of consistent monthly data acquisition and (significant) data gaps. The most prominent feature is the large time gap around 2017-2018, where the gap extends up to 12 months. This significant gap corresponds to the end of the original GRACE mission and the transition period before the launch of the GRACE Follow-On (GRACE-FO) mission. During this period, there was an inability to acquire data, as the original GRACE satellites were decommissioned and the new GRACE-FO satellites were not yet operational. Generally, a temporal resolution of approximately 1 month (which is mostly the case) is observed, aligning with the optimal requirement proposed by GCOS (2022).\n",
    "\n",
    "Let us have this quantified:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "befeb890-a302-4ba5-9a02-8c39789e1536",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The start date of the time series is 16/04/2002\n",
      "The  end  date of the time series is 17/12/2022\n",
      "The amount of months with mass change measurements that is expected between these two dates is 248\n",
      "The amount of months with mass change measurements that is present between these two dates is 213\n",
      "For a consistent monthly temporal resolution, the amount of months with missing data is 14.11%.\n"
     ]
    }
   ],
   "source": [
    "start, end = ds[\"time\"].isel(time=[0, -1]).dt.strftime(\"%d/%m/%Y\").values.tolist()\n",
    "\n",
    "for string, date in zip((\"start\", \"end\"), (start, end)):\n",
    "    print(f\"The {string:^5} date of the time series is\", date)\n",
    "\n",
    "expected = len(pd.date_range(start, end, freq=\"ME\", inclusive=\"both\"))\n",
    "actual = len(set(ds[\"time\"].dt.strftime(\"%Y%m\").values))\n",
    "for string, date in zip((\"expected\", \"present\"), (expected, actual)):\n",
    "    print(f\"The amount of months with mass change measurements that is {string} between these two dates is\", date)\n",
    "\n",
    "missing = 100 * abs(expected - actual) / expected\n",
    "print(f\"For a consistent monthly temporal resolution, the amount of months with missing data is {missing:.2f}%.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3af2dd33-7b2c-4f6f-947c-7668ebeebc55",
   "metadata": {},
   "source": [
    "Concerning spatial coverage, a significant challenge in analyzing the ice sheet's mass changes (especially for the GrIS) is deciding whether to include the peripheral glaciers and ice caps. The GRACE(-FO) GMB data include all ice masses in Greenland (and Antarctica) due to the coarse spatial resolution of several hundred kilometers during the data acquisition, which prevents differentiation between closely situated ice bodies. As a result, the mass changes of Greenland's peripheral glaciers and ice caps, which contribute approximately 30-35 Gt/year (Otosaka et al., 2023), are included in these measurements. To exclude these peripheral areas from the GRACE(-FO) time series, a scaling factor of 0.84 is often used for the GrIS (Bolch et al., 2013; Colgan et al., 2015). It must be furthermore noted that only grounded ice mass changes are considered in the GMB dataset, and that mass changes of floating ice are not considered (which is, however, relatively limited for the GrIS but can be significant for the AIS). \n",
    "\n",
    "The lack of downloadable gridded data further complicates the spatial resolution issue, although such pixel-by-pixel data are available from other sources like the TU Dresden website. The currently available data are provided as time series for the entire ice sheet's and their basins, which is too coarse to meet GCOS requirements and poses challenges, for example for ice sheet models that require gridded inputs. Moreover, the coarse spatial resolution of GRACE(-FO) data during their acquisition (several hundred kilometers) can obscure the boundaries between different basins, making it difficult to accurately assign mass changes to specific regions due to leakage errors, such as those influenced by the proximity of Canadian ice caps in the case of Greenland."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12c97e87-7e1c-40dd-bf6a-8e8787bb53bb",
   "metadata": {},
   "source": [
    "### ❄️ Ice sheet mass changes (linear and quadratic) trends and sea level contribution over time"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec126511-9213-46be-8ddf-a96e6568cbd2",
   "metadata": {},
   "source": [
    "With the imformation above, let us now go on and calculate linear and quadratic trends for the ice sheet mass change product:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "cd23e5aa-6c72-4a7d-bcb8-6ef3fcf97bac",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cumulative mass change of the Greenland Ice Sheet from GRACE(-FO):\n",
      "\tThe slope of the ice sheet mass change is -251.329 Gt/yr.\n",
      "\tThe trend is significant at an alpha level of 0.05, i.e. a monotonic trend is present.\n",
      "\tThe acceleration of the ice sheet mass change is 3.240 Gt/yr^2.\n",
      "Cumulative mass change of the Antarctic Ice Sheet from GRACE(-FO):\n",
      "\tThe slope of the ice sheet mass change is -89.873 Gt/yr.\n",
      "\tThe trend is significant at an alpha level of 0.05, i.e. a monotonic trend is present.\n",
      "\tThe acceleration of the ice sheet mass change is -2.354 Gt/yr^2.\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 800x550 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(len(variables), 1, layout=\"constrained\")\n",
    "colors = {\n",
    "    \"data\": \"black\",\n",
    "    \"linear\": \"blue\",\n",
    "    \"quadratic\": \"red\"\n",
    "}\n",
    "for ax, da in zip(axs, ds.data_vars.values()):\n",
    "    da = da.dropna(\"time\")\n",
    "    print(da.attrs[\"region\"] + \":\")\n",
    "    for label, degree, color in zip(\n",
    "        (\n",
    "            \"Linear\",\n",
    "            \"Quadratic\",\n",
    "        ),\n",
    "        (1, 2),\n",
    "        (colors[\"linear\"], colors[\"quadratic\"]),\n",
    "    ):\n",
    "        # Compute coefficients\n",
    "        coeffs = da.polyfit(\"time\", degree)[\"polyfit_coefficients\"]\n",
    "\n",
    "        # Plot trends and print stats\n",
    "        equation = []\n",
    "        for deg, coeff in coeffs.groupby(\"degree\"):\n",
    "            coeff = coeff.squeeze() * (year_to_ns**deg)\n",
    "            if deg == degree:\n",
    "                if deg == 1:\n",
    "                    quantity = \"slope\"\n",
    "                    units = \"Gt/yr\"\n",
    "                elif deg == 2:\n",
    "                    quantity = \"acceleration\"\n",
    "                    units = \"Gt/yr^2\"\n",
    "                else:\n",
    "                    raise ValueError(f\"{deg=}\")\n",
    "                print(\n",
    "                    f\"\\tThe {quantity} of the ice sheet mass change is {degree*coeff:.3f} {units}.\"\n",
    "                )\n",
    "                if deg == 1:\n",
    "                    _, p_value = scipy.stats.kendalltau(da[\"time\"], da)\n",
    "                    significance_level = 0.05\n",
    "                    is_significant = p_value < significance_level\n",
    "                    print(\n",
    "                        \" \".join(\n",
    "                            [\n",
    "                                \"\\tThe trend\",\n",
    "                                \"is significant\"\n",
    "                                if is_significant\n",
    "                                else \"is not significant\",\n",
    "                                f\"at an alpha level of {significance_level}, i.e. a monotonic trend\",\n",
    "                                \"is present.\" if is_significant else \"is not present.\",\n",
    "                            ]\n",
    "                        )\n",
    "                    )\n",
    "            equation.append(\n",
    "                f\"{float(coeff):+.3f}{'x' if deg else ''}{f'$^{deg}$' if deg>1 else ''}\"\n",
    "            )\n",
    "        label = f\"{label}: {' '.join(equation[::-1])}\"\n",
    "        fit = xr.polyval(da[\"time\"], coeffs)\n",
    "        fit.plot(label=label, ax=ax, color=color)\n",
    "    da.plot(label=\"Ice sheet mass change data\", ax=ax, color='k')\n",
    "    ax.set_title(f\"{da.attrs['region']}\")\n",
    "    ax.set_xlim(np.min(ds[\"time\"]), np.max(ds[\"time\"]))\n",
    "    ax.grid(color='#95a5a6', linestyle='-', alpha=0.25)\n",
    "    ax.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "43c3b04e-3c5d-4ea6-80e8-d087ed296d96",
   "metadata": {},
   "source": [
    "The GRACE(-FO) data plots illustrate the cumulative mass changes of the Greenland and Antarctic Ice Sheets over time. For the Greenland Ice Sheet, the linear trend indicates a significant and consistent annual mass loss of approximately 250 gigatonnes per year, with a statistically significant monotonic trend at an alpha level of 0.05. Hence, the analysis reveales accelerated mass losses from 2002 until 2012-2013, followed by a slowdown until the years 2017-2018. Then, for the more recent period from 2019 onwards up until now, mass loss acceleration is again reoccurring (e.g. Sasgen et al., 2020; Otosaka et al., 2023). Similarly, the Antarctic Ice Sheet data show a significant linear trend, with an annual mass loss of approximately 90 gigatonnes per year. This trend is also statistically significant at an alpha level of 0.05. Mass changes were fairly stable fom 2002 until 2007, but slightly accelerating mass loss has occurred after 2007-2008. During the more recent years, a slight deceleration in the mass changes is noted (e.g. Sasgen et al., 2019; Fox-Kemper et al., 2021).. Both the Greenland and Antarctic Ice Sheets thus exhibit significant ongoing mass loss, with the statistical significance of the trends underscoring the robustness of these findings. The linear and quadratic trend lines, depicted in red and green respectively, provide a clear visual representation of these trends, highlighting the critical changes occurring in the polar regions \n",
    "\n",
    "We furthermore note again that GRACE(-FO) cannot detect changes in floating ice and grounded ice below sea level. Mass change processes occurring past the grounding line, such as a retreating calving front, ocean-induced melt beneath the ice shelves, as well as changes to the part of the ice that is occupied by water (or in other words ice below buouyancy) will therefore not be detectable (because it is occupied by the same mass of water). In that regard, GMB measurements by GRACE(-FO) are immediately convertible to sea level contributions. These changes in mean global sea level can be caused by various processes. Mass changes of ice sheets are only a part of the total contribution:\n",
    "\n",
    "$\\Delta SL = \\Delta SL_{steric} + \\Delta SL_{VLM} + \\Delta SL_{glac} + \\Delta SL_{IS} + \\Delta SL_{LWS} + \\Delta SL_{other}$\n",
    "\n",
    "where $\\Delta SL_{steric}$ is the term related to changes in density caused by variations in temperature (thermosteric) and salinity (halosteric), $\\Delta SL_{VLM}$ is the term related to changes due to vertical land motion, $\\Delta SL_{glac}$ and $\\Delta SL_{IS}$ are related to mass addition/removal by glaciers, ice caps, and ice sheets, $\\Delta SL_{LWS}$ is a land water storage term that includes processes such as trends in precipitation minus evaporation, and lastly, $\\Delta SL_{other}$ quantifies the other remaining and less significant processes contributing to changes of mean global sea level. For the contributions of ice sheets, we assume that 361.8 Gt of ice will raise global sea levels by 1 mm (where 361.8 Gt of ice is equivalent to 394.67 km$^3$ ice):\n",
    "\n",
    "$\n",
    "\\Delta SL_{IS} = h_{SLE} \n",
    "$\n",
    "[mm]\n",
    "$\n",
    "= -\\dfrac{\\Delta M_{GRACE}}{361.8}\n",
    "$\n",
    "\n",
    "where $\\Delta M_{GRACE}$ is the cumulative mass change of the ice sheets measured by GRACE(-FO) in Gt. Let us plot this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "2ce3fa4c-e0ad-4615-a3a1-345ef76d2009",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cumulative global sea level contribution of the Greenland Ice Sheet from GRACE(-FO):\n",
      "\tThe slope of the global sea level contribution is 0.695 mm/yr.\n",
      "\tThe trend is significant at an alpha level of 0.05, i.e. a monotonic trend is present.\n",
      "\tThe acceleration of the global sea level contribution is -0.009 mm/yr^2.\n",
      "Cumulative global sea level contribution of the Antarctic Ice Sheet from GRACE(-FO):\n",
      "\tThe slope of the global sea level contribution is 0.248 mm/yr.\n",
      "\tThe trend is significant at an alpha level of 0.05, i.e. a monotonic trend is present.\n",
      "\tThe acceleration of the global sea level contribution is 0.007 mm/yr^2.\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 800x550 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(len(variables), 1, layout=\"constrained\")\n",
    "colors = {\n",
    "    \"data\": \"black\",\n",
    "    \"linear\": \"blue\",\n",
    "    \"quadratic\": \"red\"\n",
    "}\n",
    "# Convert mass change to global sea level change\n",
    "ds_SL = -(ds/361.8)\n",
    "for i, (var, da) in enumerate(ds_SL.data_vars.items()):\n",
    "    if i == 0:\n",
    "        da.attrs[\"region\"] = \"Cumulative global sea level contribution of the Greenland Ice Sheet from GRACE(-FO)\"\n",
    "\n",
    "    elif i == 1:\n",
    "        da.attrs[\"region\"] = \"Cumulative global sea level contribution of the Antarctic Ice Sheet from GRACE(-FO)\"\n",
    "    else:\n",
    "        da.attrs[\"region\"] = da.attrs[\"long_name\"].split(\"_\", 1)[0].title()\n",
    "    da.attrs[\"long_name\"] = \"Sea level contribution (mm)\"\n",
    "# Plot the data and trends\n",
    "for ax, da in zip(axs, ds_SL.data_vars.values()):\n",
    "    da = da.dropna(\"time\")\n",
    "    print(da.attrs[\"region\"] + \":\")\n",
    "    for label, degree, color in zip(\n",
    "        (\n",
    "            \"Linear\",\n",
    "            \"Quadratic\",\n",
    "        ),\n",
    "        (1, 2),\n",
    "        (colors[\"linear\"], colors[\"quadratic\"]),\n",
    "    ):\n",
    "        # Compute coefficients\n",
    "        coeffs = da.polyfit(\"time\", degree)[\"polyfit_coefficients\"]\n",
    "\n",
    "        # Plot trends and print stats\n",
    "        equation = []\n",
    "        for deg, coeff in coeffs.groupby(\"degree\"):\n",
    "            coeff = coeff.squeeze() * (year_to_ns**deg)\n",
    "            if deg == degree:\n",
    "                if deg == 1:\n",
    "                    quantity = \"slope\"\n",
    "                    units = \"mm/yr\"\n",
    "                elif deg == 2:\n",
    "                    quantity = \"acceleration\"\n",
    "                    units = \"mm/yr^2\"\n",
    "                else:\n",
    "                    raise ValueError(f\"{deg=}\")\n",
    "                print(\n",
    "                    f\"\\tThe {quantity} of the global sea level contribution is {degree*coeff:.3f} {units}.\"\n",
    "                )\n",
    "                if deg == 1:\n",
    "                    _, p_value = scipy.stats.kendalltau(da[\"time\"], da)\n",
    "                    significance_level = 0.05\n",
    "                    is_significant = p_value < significance_level\n",
    "                    print(\n",
    "                        \" \".join(\n",
    "                            [\n",
    "                                \"\\tThe trend\",\n",
    "                                \"is significant\"\n",
    "                                if is_significant\n",
    "                                else \"is not significant\",\n",
    "                                f\"at an alpha level of {significance_level}, i.e. a monotonic trend\",\n",
    "                                \"is present.\" if is_significant else \"is not present.\",\n",
    "                            ]\n",
    "                        )\n",
    "                    )\n",
    "            equation.append(\n",
    "                f\"{float(coeff):+.3f}{'x' if deg else ''}{f'$^{deg}$' if deg>1 else ''}\"\n",
    "            )\n",
    "        label = f\"{label}: {' '.join(equation[::-1])}\"\n",
    "        fit = xr.polyval(da[\"time\"], coeffs)\n",
    "        fit.plot(label=label, ax=ax, color=color)\n",
    "    da.plot(label=\"Ice sheet mass change data\", ax=ax, color='k')\n",
    "    ax.set_title(f\"{da.attrs['region']}\")\n",
    "    ax.set_xlim(np.min(ds_SL[\"time\"]), np.max(ds_SL[\"time\"]))\n",
    "    ax.grid(color='#95a5a6', linestyle='-', alpha=0.25)\n",
    "    ax.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff66bf78-0dfa-447e-ba4d-7cbf73a1b056",
   "metadata": {},
   "source": [
    "The provided graphs illustrate the cumulative global sea level contributions of the Greenland and Antarctic Ice Sheets based on GRACE(-FO) data, along with linear and quadratic trend analyses. These plots provide insights into the rate and nature of sea level contributions from these ice sheets over time. Overall, these graphs emphasize the significant and ongoing contributions of both the Greenland and Antarctic Ice Sheets to global sea level rise. The linear trends and their significance highlight a consistent ongoing increase in sea level contributions, with Greenland contributing more significantly compared to Antarctica. The trends and their magnitudes observed in the GRACE(-FO) data for both the Greenland and Antarctic Ice Sheets are broadly consistent with the findings reported in the literature (e.g. Bamber et al., 2018; Rignot et al., 2019; Fox-Kemper et al., 2021), highlighting the reliability and quality-richness of GRACE(-FO) data with respect to capturing significant ice mass changes and their impact on global sea level rise. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8fd5aa3b-8889-49ee-8129-b4269769e446",
   "metadata": {},
   "source": [
    "### 📌 Implications for use of GRACE(-FO) mass change data as global climate change and sea level change indicators"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f3aae74-ae48-44bd-899c-7caa48e6c807",
   "metadata": {},
   "source": [
    "Let us now consider the suitability of GRACE(-FO) data with respect to the specific use case and user question. When measured over a long period and at extended geographical scales (distinct ice sheet basins or over the complete ice sheet), trends in ice sheet mass changes or mass balances can be considered a clear indicator of global climate change. However, for these trends to be accruate, representative and reliable, the dataset should have an adequate spatial/temporal resolution and coverage (extent). From the above analysis, it can be stated that the dataset provides a suitable spatial and temporal extent (coverage) to capture both linear and quadratic trends in ice sheet mass changes, enabling detailed analysis of long-term basin-scale or ice sheet-wide mass change trends. \n",
    "\n",
    "One of the key strengths of GRACE(-FO) is its spatial coverage, allowing for the monitoring of ice mass changes across all major ice sheets, including remote and inaccessible regions. Unlike other remote sensing methods that infer mass changes from surface elevation changes or ice flow velocities, GRACE(-FO) directly measures variations or anomalies in the Earth's gravitational field, which are directly related to changes in mass and a redistribution of that mass. Coupled with the monthly temporal resolution of GRACE(-FO) data, the dataset enables the detection of seasonal and interannual variations in ice sheet mass balance. The dataset’s comprehensive temporal (> 20 years) and spatial (ice sheet-wide) coverage of the world’s ice sheets furthermore ensures that these trends are meaningful and can be assessed at both regional (basins) and ice sheet-wide spatial scales. Despite the fact that the Intergovernmental Panel on Climate Change (IPCC) uses 30 years as a standard period for climate normals and trend analysis to ensure that the analysis captures meaningful climatic changes, the temporal coverage since 2002 already allows for clear temporal patterns to be detected. The continuity of data from GRACE (2002-2017) to GRACE-FO (2018-present) thus provides a long-term, consistent dataset that is crucial for detecting trends and changes over time. The statistical significance of these trends further underscores the reliability of using this dataset to monitor climatic changes and global water cycle changes. \n",
    "\n",
    "However, the detection of gravity-derived ice mass changes also has its limitations of which the user should take note before using the product. The coarse spatial resolution (several hundred kilometers) during data acquisition limits its ability to capture small-scale patterns, as well as to separate closely situated ice mass bodies, such as the Canadian ice caps around Greenland. This can result in signal leakage between adjacent regions, complicating the attribution of mass changes to specific sources. Additionally, GRACE(-FO) measurements can be affected by uncertainties related to the Earth’s gravitational field (e.g. due to the shift of the Earth’s center of mass, or due to the influence of the atmosphere and oceans on the Earth’s gravity field), as well as by mass changes not related to ice, such as glacial isostatic adjustment, requiring correction that introduces relatively high uncertainties. Another large problem with the dataset is that no pixel-by-pixel mass change and error products are included for the ice sheets. Users should take into account the inability to infer mass change trends at a spatial resolution finer than the basin-scale. \n",
    "\n",
    "Apart form that, users should also acknowledge what GRACE(-FO) ice mass changes actually represent. What GRACE(-FO) actually detects are patterns of mass redistribution, indicating that a material should be redistributed (e.g. by liquid discharge) in order for GRACE(-FO) to be able to detect gravity anomalies and the corresponding mass changes over certain locations. Only grounded ice mass changes above sea level are considered in the dataset, mass changes of floating ice and ice grounded below sea level (ice below buyoancy) are not considered because it gets replaced by a mass-equivalent amount of water (which is, however, relatively limited for the GrIS but can be significant for the AIS). GRACE(-FO) data are therefore considered to be the sum of mass changes driven by changing rates of solid ice discharge (i.e. ice dynamics) and mass changes driven by changing rates of runoff and accumulation (basal, internal and surface conditions) over grounded ice above sea level. For the GrIS, the mass changes therefore include signals from the peripheral glaciers and ice caps, but for the AIS this excludes data for the ice shelves. In the sense of global water cycle changes, this means that GMB measurements by GRACE(-FO) are immediately convertible to sea level contributions.\n",
    "\n",
    "The time series of the basin-scale and ice-sheet wide GMB products are thus found to be suitable to derive mean, variability and trends (i.e. climate change signals), as (1) the amount of missing data is relatively limited (despite the gap between GRACE and GRACE-FO in 2017/2018), (2) the temporal resolution is generally consistent at 1-monthly spaced time intervals, and (3) the number of consecutive years is generally sufficient to filter out inter- and intra-annual variability. The GMB products are thus found to be highly applicable to derive mass changes of ice above buyoancy over time and to, for example, assess the corresponding impact on global sea level changes. Due to the high error and uncertainty values, however, the GMB product should be handled with care. In conclusion, GRACE(-FO) provides valueable data on ice sheet mass changes, making it an essential tool for understanding and quantifying globale climate change and global water cycle changes. While it has certain limitations that have to be taken into account during quality assessment, its strengths as an ice sheet-wide, direct ice mass change measurement tool make it essential to capture ice sheet mass changes and their contributions to sea level rise. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae9b8cb7-c8ac-4882-bb6e-8ddcf30095c3",
   "metadata": {},
   "source": [
    "## 🔍 If you want to know more"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c016be77-c0fb-43ea-a978-d8fc3cdbc191",
   "metadata": {},
   "source": [
    "### Key resources"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9eefe6b1-8055-4143-984f-a8188f9e4c37",
   "metadata": {},
   "source": [
    "- \"Gravimetric mass balance data for the Antarctic and Greenland ice sheets from 2003 to 2022 derived from satellite observations\" on the CDS.\n",
    "- [C3S EQC custom functions](https://github.com/bopen/c3s-eqc-automatic-quality-control/tree/main/c3s_eqc_automatic_quality_control), `c3s_eqc_automatic_quality_control` prepared by [BOpen](https://www.bopen.eu)."
   ]
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  {
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   "source": [
    "### References"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20c94bbb-7c3d-4614-9454-70cc41fa94ee",
   "metadata": {},
   "source": [
    "- Bamber, J. L., Westaway, R. M., Marzeion, B., and Wouters, B. (2018). The land ice contribution to sea level during the satellite era. Environ. Res. Lett. 13, https://doi.org/10.1088/1748-9326/aac2f0.\n",
    "\n",
    "- Bolch, T., Sørensen, L.S., Simonsen, S. B., Mölg, N., Machguth, H., Rastner, P., & Paul, F. (2013). Mass loss of Greenland's glaciers and ice caps 2003–2008 revealed from ICESat laser altimetry data. Geophysical Research Letters, 40(5), 875-881. https://doi.org/10.1002/grl.50270.\n",
    "\n",
    "- Colgan, W., Abdalati, W., Citterio, M., Csatho, B., Fettweis, X., Luthcke, S., Moholdt, G., Simonsen, S.B., and Stober, M. (2015). Hybrid glacier Inventory, Gravimetry and Altimetry (HIGA) mass balance product for Greenland and the Canadian Arctic. Remote Sensing of Environment, 168, 24–39. https://doi.org/10.1016/j.rse.2015.06.016.\n",
    "\n",
    "- Forsberg, R., Sørensen, L.S. and Simonsen, S.B. (2017). Greenland and Antarctica Ice Sheet Mass Changes and Effects on Global Sea Level. Surv. Geophys., 38, 89–104. https://doi.org/10.1007/s10712-016-9398-7.\n",
    "\n",
    "- Fox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu (2021). Ocean, Cryosphere and Sea Level Change. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1211–1362, https://doi.org/110.1017/9781009157896.011.\n",
    "\n",
    "- Groh, A., Horwath, M., Horvath, A., Meister, R., Sørensen, L.S., Barletta, V.R., Forsberg, R., Wouters, B., Ditmar, P., Ran, J., Klees, R., Su, X., Shang, K., Guo, J., Shum, C.K., Schrama, E., and Shepherd, A. (2019). Evaluating GRACE Mass Change Time Series for the Antarctic and Greenland Ice Sheet, Geosciences, 9(10). https://doi.org/10.3390/geosciences9100415.\n",
    "\n",
    "- Otosaka, I. N., Shepherd, A., Ivins, E. R., Schlegel, N.-J., Amory, C., van den Broeke, M. R., Horwath, M., Joughin, I., King, M. D., Krinner, G., Nowicki, S., Payne, A. J., Rignot, E., Scambos, T., Simon, K. M., Smith, B. E., Sørensen, L. S., Velicogna, I., Whitehouse, P. L., A, G., Agosta, C., Ahlstrøm, A. P., Blazquez, A., Colgan, W., Engdahl, M. E., Fettweis, X., Forsberg, R., Gallée, H., Gardner, A., Gilbert, L., Gourmelen, N., Groh, A., Gunter, B. C., Harig, C., Helm, V., Khan, S. A., Kittel, C., Konrad, H., Langen, P. L., Lecavalier, B. S., Liang, C.-C., Loomis, B. D., McMillan, M., Melini, D., Mernild, S. H., Mottram, R., Mouginot, J., Nilsson, J., Noël, B., Pattle, M. E., Peltier, W. R., Pie, N., Roca, M., Sasgen, I., Save, H. V., Seo, K.-W., Scheuchl, B., Schrama, E. J. O., Schröder, L., Simonsen, S. B., Slater, T., Spada, G., Sutterley, T. C., Vishwakarma, B. D., van Wessem, J. M., Wiese, D., van der Wal, W., and Wouters, B. (2023). Mass balance of the Greenland and Antarctic ice sheets from 1992 to 2020, Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023.\n",
    "\n",
    "- Sasgen, I., Konrad, H., Helm, V., and Grosfeld, K. (2019). High-Resolution Mass Trends of the Antarctic Ice Sheet through a Spectral Combination of Satellite Gravimetry and Radar Altimetry Observations. Remote Sensing, 11(2):144. https://doi.org/10.3390/rs11020144.\n",
    "\n",
    "- Sasgen, I., Wouters, B., Gardner, A.S., King, M.D., Tedesco, M., Landerer, F.W., Dahle, C., Save, H., and Fettweis, X. (2020). Return to rapid ice loss in Greenland and record loss in 2019 detected by the GRACE-FO satellites. Commun. Earth Environ., 1, no. 1, 8, https://doi.org/10.1038/s43247-020-0010-1.\n",
    "\n",
    "- Rignot, E., Mouginot, J., Scheuchl, B., Van Den Broeke, M., Van Wessem, M. J., and Morlighem, M. (2019). Four decades of Antarctic Ice Sheet mass balance from 1979–2017. Proceedings of the National Academy of Sciences, 116(4), 1095–1103. https://doi.org/10.1073/pnas.1812883116."
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