From 00c7182325fcdffb44db0da6aefe609e8ea4f308 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Sun, 1 Oct 2023 14:16:45 +0100
Subject: [PATCH 1/8] [Condalock] Update Linux condalock file (#3365)

Co-authored-by: valeriupredoi <valeriupredoi@users.noreply.github.com>
---
 conda-linux-64.lock | 120 ++++++++++++++++++++++----------------------
 1 file changed, 60 insertions(+), 60 deletions(-)

diff --git a/conda-linux-64.lock b/conda-linux-64.lock
index 128ace6209..8f862fe311 100644
--- a/conda-linux-64.lock
+++ b/conda-linux-64.lock
@@ -59,7 +59,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libffi-3.4.2-h7f98852_5.tar.bz2#
 https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-13.2.0-ha4646dd_2.conda#78fdab09d9138851dde2b5fe2a11019e
 https://conda.anaconda.org/conda-forge/linux-64/libiconv-1.17-h166bdaf_0.tar.bz2#b62b52da46c39ee2bc3c162ac7f1804d
 https://conda.anaconda.org/conda-forge/linux-64/libjpeg-turbo-2.1.5.1-hd590300_1.conda#323e90742f0f48fc22bea908735f55e6
-https://conda.anaconda.org/conda-forge/linux-64/libnsl-2.0.0-h7f98852_0.tar.bz2#39b1328babf85c7c3a61636d9cd50206
+https://conda.anaconda.org/conda-forge/linux-64/libnsl-2.0.0-hd590300_1.conda#854e3e1623b39777140f199c5f9ab952
 https://conda.anaconda.org/conda-forge/linux-64/libnuma-2.0.16-h0b41bf4_1.conda#28bfe2cb11357ccc5be21101a6b7ce86
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@@ -81,7 +81,7 @@ https://conda.anaconda.org/conda-forge/linux-64/nspr-4.35-h27087fc_0.conda#da0ec
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 https://conda.anaconda.org/conda-forge/linux-64/p7zip-16.02-h9c3ff4c_1001.tar.bz2#941066943c0cac69d5aa52189451aa5f
-https://conda.anaconda.org/conda-forge/linux-64/pixman-0.40.0-h36c2ea0_0.tar.bz2#660e72c82f2e75a6b3fe6a6e75c79f19
+https://conda.anaconda.org/conda-forge/linux-64/pixman-0.42.2-h59595ed_0.conda#700edd63ccd5fc66b70b1c028cea9a68
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@@ -133,9 +133,9 @@ https://conda.anaconda.org/conda-forge/linux-64/pcre2-10.40-hc3806b6_0.tar.bz2#6
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-https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.12-h27826a3_0.tar.bz2#5b8c42eb62e9fc961af70bdd6a26e168
+https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-h2797004_0.conda#513336054f884f95d9fd925748f41ef3
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-https://conda.anaconda.org/conda-forge/linux-64/udunits2-2.2.28-h40f5838_1.conda#85552d64cb49f12781668779efc738ec
+https://conda.anaconda.org/conda-forge/linux-64/udunits2-2.2.28-h40f5838_2.conda#bafaeb2c6cae03d330ac71ef893fa431
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@@ -157,7 +157,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libarchive-3.6.2-h039dbb9_1.cond
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-https://conda.anaconda.org/conda-forge/linux-64/libhwloc-2.9.2-default_h554bfaf_1009.conda#9369f407667517fe52b0e8ed6965ffeb
+https://conda.anaconda.org/conda-forge/linux-64/libhwloc-2.9.3-default_h554bfaf_1009.conda#f36ddc11ca46958197a45effdd286e45
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@@ -168,7 +168,7 @@ https://conda.anaconda.org/conda-forge/linux-64/orc-1.9.0-h385abfd_1.conda#2cd5a
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-https://conda.anaconda.org/conda-forge/linux-64/tktable-2.10-h0c5db8f_3.conda#f3936dae9fc1423662ffacd0429e2cc9
+https://conda.anaconda.org/conda-forge/linux-64/tktable-2.10-h0c5db8f_5.conda#9464044754ea25557a9c93f0327d90a6
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@@ -178,7 +178,7 @@ https://conda.anaconda.org/conda-forge/linux-64/atk-1.0-2.38.0-hd4edc92_1.tar.bz
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-https://conda.anaconda.org/conda-forge/linux-64/backports.zoneinfo-0.2.1-py311h38be061_7.tar.bz2#ec62b3c5b953cb610f5e2b09cd776caf
+https://conda.anaconda.org/conda-forge/linux-64/backports.zoneinfo-0.2.1-py311h38be061_8.conda#5384590f14dfe6ccd02811236afc9f8e
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@@ -191,11 +191,11 @@ https://conda.anaconda.org/conda-forge/noarch/colorama-0.4.6-pyhd8ed1ab_0.tar.bz
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-https://conda.anaconda.org/conda-forge/linux-64/cython-3.0.2-py311hb755f60_0.conda#81d4eacf7eb2d40beee33aa71e8f94ad
+https://conda.anaconda.org/conda-forge/linux-64/cython-3.0.2-py311hb755f60_2.conda#35878142ccd98f076942b40ffb3cfbab
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-https://conda.anaconda.org/conda-forge/linux-64/docutils-0.20.1-py311h38be061_1.conda#ff1b48b5b802afe76597197113b8e64d
+https://conda.anaconda.org/conda-forge/linux-64/docutils-0.20.1-py311h38be061_2.conda#33f8066e53679dd4be2355fec849bf01
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@@ -206,8 +206,8 @@ https://conda.anaconda.org/conda-forge/noarch/fasteners-0.17.3-pyhd8ed1ab_0.tar.
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-https://conda.anaconda.org/conda-forge/noarch/fsspec-2023.9.1-pyh1a96a4e_0.conda#d69753ff6ee3c84a6638921dd95db662
+https://conda.anaconda.org/conda-forge/linux-64/frozenlist-1.4.0-py311h459d7ec_1.conda#23d0b2d02252b32ee14e5063ccfb41e2
+https://conda.anaconda.org/conda-forge/noarch/fsspec-2023.9.2-pyh1a96a4e_0.conda#9d15cd3a0e944594ab528da37dc72ecc
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@@ -216,8 +216,8 @@ https://conda.anaconda.org/conda-forge/noarch/idna-3.4-pyhd8ed1ab_0.tar.bz2#3427
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+https://conda.anaconda.org/conda-forge/linux-64/kiwisolver-1.4.5-py311h9547e67_1.conda#2c65bdf442b0d37aad080c8a4e0d452f
+https://conda.anaconda.org/conda-forge/linux-64/lazy-object-proxy-1.9.0-py311h459d7ec_1.conda#7cc99d87755a9e64586a6004c5f0f534
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@@ -227,12 +227,12 @@ https://conda.anaconda.org/conda-forge/linux-64/libpq-15.3-hbcd7760_1.conda#8afb
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+https://conda.anaconda.org/conda-forge/linux-64/msgpack-python-1.0.6-py311h9547e67_0.conda#e826b71bf3dc8c91ee097663e2bcface
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@@ -246,7 +246,7 @@ https://conda.anaconda.org/conda-forge/noarch/pandocfilters-1.5.0-pyhd8ed1ab_0.t
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+https://conda.anaconda.org/conda-forge/linux-64/psutil-5.9.5-py311h459d7ec_1.conda#490d7fa8675afd1aa6f1b2332d156a45
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@@ -257,16 +257,16 @@ https://conda.anaconda.org/conda-forge/noarch/pyshp-2.3.1-pyhd8ed1ab_0.tar.bz2#9
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 https://conda.anaconda.org/conda-forge/noarch/chart-studio-1.1.0-pyh9f0ad1d_0.tar.bz2#acd9a12a35e5a0221bdf39eb6e4811dc
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-https://conda.anaconda.org/conda-forge/linux-64/contourpy-1.1.1-py311h9547e67_0.conda#db5b3b0093d0d4565e5c89578108402e
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 https://conda.anaconda.org/conda-forge/noarch/identify-2.5.29-pyhd8ed1ab_0.conda#5bdbb1cb692649720b60f261b41760cd
@@ -424,22 +424,22 @@ https://conda.anaconda.org/conda-forge/noarch/imageio-2.31.1-pyh24c5eb1_0.conda#
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+https://conda.anaconda.org/conda-forge/linux-64/jupyter_core-5.3.2-py311h38be061_0.conda#4e4341e940c0dfa1038c1a2d11fd8c3e
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-https://conda.anaconda.org/conda-forge/noarch/pylint-2.17.5-pyhd8ed1ab_0.conda#30dc94b05de470e3b579d73d64127656
+https://conda.anaconda.org/conda-forge/noarch/pooch-1.7.0-pyhd8ed1ab_4.conda#3cdaf7af08850933662b1e228bc6b5bc
+https://conda.anaconda.org/conda-forge/noarch/pylint-2.17.6-pyhd8ed1ab_0.conda#71d8c641a688ae0fbe6e4ebba44ec405
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-https://conda.anaconda.org/conda-forge/linux-64/pywavelets-1.4.1-py311hcb2cf0a_0.conda#272ca0c28df344037ba2c4982d4e4791
+https://conda.anaconda.org/conda-forge/linux-64/pywavelets-1.4.1-py311h1f0f07a_1.conda#86b71ff85f3e4c8a98b5bace6d9c4565
 https://conda.anaconda.org/conda-forge/noarch/requests-cache-1.1.0-pyhd8ed1ab_0.conda#57b89064c125bb9d0e533e018c3eb17a
-https://conda.anaconda.org/conda-forge/linux-64/scipy-1.11.2-py311h64a7726_1.conda#58af16843fc4469770bdbaf45d3a19de
+https://conda.anaconda.org/conda-forge/linux-64/scipy-1.11.3-py311h64a7726_0.conda#756e8ac1d784f704c0b22559b4bff7b0
 https://conda.anaconda.org/conda-forge/noarch/seawater-3.3.4-py_1.tar.bz2#a9e101e1601faf5e5a119ab2bd7617a4
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 https://conda.anaconda.org/conda-forge/noarch/snuggs-1.4.7-py_0.tar.bz2#cb83a3d6ecf73f50117635192414426a
@@ -449,28 +449,28 @@ https://conda.anaconda.org/conda-forge/noarch/yapf-0.40.1-pyhd8ed1ab_0.conda#f26
 https://conda.anaconda.org/conda-forge/linux-64/aws-sdk-cpp-1.10.57-hbc2ea52_17.conda#452c7b08c21eea2ef01f4fd364d6affc
 https://conda.anaconda.org/conda-forge/noarch/bokeh-3.2.2-pyhd8ed1ab_0.conda#30488151f591379db656250b3f5fc0c6
 https://conda.anaconda.org/conda-forge/linux-64/cf-units-3.2.0-py311h1f0f07a_0.conda#43a71a823583d75308eaf3a06c8f150b
-https://conda.anaconda.org/conda-forge/noarch/distributed-2023.9.2-pyhd8ed1ab_0.conda#ddb4fd6105b4005b312625cef210ba67
+https://conda.anaconda.org/conda-forge/noarch/distributed-2023.9.3-pyhd8ed1ab_0.conda#543fafdd7b325bf16199235ee5f20622
 https://conda.anaconda.org/conda-forge/linux-64/eccodes-2.30.2-h1f30a5c_0.conda#21ee8444a7f629924ea8cfe52a622cbd
 https://conda.anaconda.org/conda-forge/linux-64/esmf-8.4.2-nompi_h20110ff_0.conda#11f5169aeff54ad7277476be8ba19ff7
 https://conda.anaconda.org/conda-forge/linux-64/gdal-3.7.0-py311h281082f_2.conda#fde4fad3c517cc80f32995696f45198d
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 https://conda.anaconda.org/conda-forge/linux-64/librsvg-2.56.3-h98fae49_0.conda#620e754f4344f4c27259ff460a2b9c50
-https://conda.anaconda.org/conda-forge/linux-64/matplotlib-base-3.8.0-py311h54ef318_0.conda#b67672c2f39ef2912a1814e29e42c7ca
+https://conda.anaconda.org/conda-forge/linux-64/matplotlib-base-3.8.0-py311h54ef318_1.conda#20d79e2fe53b49b399f3d36977b05abb
 https://conda.anaconda.org/conda-forge/noarch/myproxyclient-2.1.0-pyhd8ed1ab_2.tar.bz2#363b0816e411feb0df925d4f224f026a
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 https://conda.anaconda.org/conda-forge/noarch/patsy-0.5.3-pyhd8ed1ab_0.tar.bz2#50ef6b29b1fb0768ca82c5aeb4fb2d96
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-https://conda.anaconda.org/conda-forge/noarch/pre-commit-3.4.0-pyha770c72_1.conda#3fb5ba328a77c9fd71197a46e7f2469a
+https://conda.anaconda.org/conda-forge/noarch/pre-commit-3.4.0-pyha770c72_2.conda#09cd3006f61e7a7054405f81362e0a5f
 https://conda.anaconda.org/conda-forge/noarch/pylint-plugin-utils-0.7-pyhd8ed1ab_0.tar.bz2#1657976383aee04dbb3ae3bdf654bb58
-https://conda.anaconda.org/conda-forge/linux-64/python-stratify-0.3.0-py311h1f0f07a_0.conda#3a00b1b08d8c01b1a3bfa686b9152df2
+https://conda.anaconda.org/conda-forge/linux-64/python-stratify-0.3.0-py311h1f0f07a_1.conda#cd36a89a048ad2bcc6d8b43f648fb1d0
 https://conda.anaconda.org/conda-forge/linux-64/r-base-4.1.3-hfabd6f2_9.conda#0ab4cf54fbddc0cc9ff260c6f77f8c84
 https://conda.anaconda.org/conda-forge/linux-64/rasterio-1.3.8-py311h41e4db2_0.conda#b35deb26af1d7e0d98438c8ac5c6b7b2
-https://conda.anaconda.org/conda-forge/linux-64/scikit-learn-1.3.0-py311hc009520_0.conda#847797c4a9c0c3363ffcfe7571dedfee
+https://conda.anaconda.org/conda-forge/linux-64/scikit-learn-1.3.1-py311hc009520_0.conda#66f1553377ee79c5cf33dad1fa9cebb4
 https://conda.anaconda.org/conda-forge/noarch/sparse-0.14.0-pyhd8ed1ab_0.conda#ee01b310177a0612554b9d20e537fdbe
-https://conda.anaconda.org/conda-forge/noarch/tifffile-2023.9.18-pyhd8ed1ab_0.conda#c24d705dfe38f0a7a5cfa51b40c3d906
-https://conda.anaconda.org/conda-forge/noarch/xarray-2023.8.0-pyhd8ed1ab_0.conda#a8104cede521616573e228c27f9edc97
+https://conda.anaconda.org/conda-forge/noarch/tifffile-2023.9.26-pyhd8ed1ab_0.conda#d133bea7d8ac17552492a0629229eeb1
+https://conda.anaconda.org/conda-forge/noarch/xarray-2023.9.0-pyhd8ed1ab_0.conda#158c89bbc0f2597f33e8ce1aea59e0ee
 https://conda.anaconda.org/conda-forge/noarch/zarr-2.16.1-pyhd8ed1ab_0.conda#59ec835edbee50266b7bdbadab7ba335
 https://conda.anaconda.org/conda-forge/linux-64/cartopy-0.22.0-py311h320fe9a_0.conda#1271b2375735e2aaa6d6770dbe2ad087
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@@ -567,7 +567,7 @@ https://conda.anaconda.org/conda-forge/noarch/prospector-1.10.2-pyhd8ed1ab_0.con
 https://conda.anaconda.org/conda-forge/linux-64/psy-simple-1.4.1-py311h38be061_2.tar.bz2#4c9101d329f6bc09c2617a80e3eb9c89
 https://conda.anaconda.org/conda-forge/noarch/py-cordex-0.6.3-pyhd8ed1ab_0.conda#de9f9392273a1e6095930a21561a37e9
 https://conda.anaconda.org/conda-forge/linux-64/pyarrow-12.0.1-py311h39c9aba_7_cpu.conda#d513ab8d10ec5f3ee45b419c836195ec
-https://conda.anaconda.org/conda-forge/linux-64/pydot-1.4.2-py311h38be061_3.tar.bz2#64a77de29fde80aef5013ddf5e62a564
+https://conda.anaconda.org/conda-forge/linux-64/pydot-1.4.2-py311h38be061_4.conda#5c223cb0d9c05552bf9d1586a92720b2
 https://conda.anaconda.org/conda-forge/linux-64/r-askpass-1.1-r41h06615bd_3.tar.bz2#c8ec8683302ad9a2345cb31ab28e6c6b
 https://conda.anaconda.org/conda-forge/linux-64/r-bigmemory-4.6.1-r41h7525677_1.tar.bz2#6a956b57b027b49b7a9ca48031a8bbd6
 https://conda.anaconda.org/conda-forge/linux-64/r-checkmate-2.2.0-r41h57805ef_0.conda#dc314ad76563387e70e0117c5398a15a
@@ -597,7 +597,7 @@ https://conda.anaconda.org/conda-forge/linux-64/r-zoo-1.8_12-r41h133d619_0.conda
 https://conda.anaconda.org/conda-forge/noarch/seaborn-0.12.2-hd8ed1ab_0.conda#50847a47c07812f88581081c620f5160
 https://conda.anaconda.org/conda-forge/noarch/xesmf-0.8.2-pyhd8ed1ab_0.conda#8e765a0eca0ce1cfa889cd9af82a23a8
 https://conda.anaconda.org/conda-forge/linux-64/xgboost-1.7.6-cuda112py311h2344cce_2.conda#97cd4e1589b8ea11e0f78d2f0c7cc217
-https://conda.anaconda.org/conda-forge/noarch/dask-2023.9.2-pyhd8ed1ab_0.conda#29e33df59c9eac1a599b9cd18d54b4d3
+https://conda.anaconda.org/conda-forge/noarch/dask-2023.9.3-pyhd8ed1ab_0.conda#5b32dc4eb1f5e3097cc33fb0e331b3a4
 https://conda.anaconda.org/conda-forge/noarch/nbconvert-pandoc-7.8.0-pyhd8ed1ab_0.conda#1dba1a577df2625a24667612a069e91c
 https://conda.anaconda.org/conda-forge/noarch/prov-2.0.0-pyhd3deb0d_0.tar.bz2#aa9b3ad140f6c0668c646f32e20ccf82
 https://conda.anaconda.org/conda-forge/noarch/psy-maps-1.4.2-pyhd8ed1ab_0.tar.bz2#3ed13103dfd46f71dc870d188bd0b276

From a6f98182d2f92703133c0d5db3cd02c16f0ad5c4 Mon Sep 17 00:00:00 2001
From: Manuel Schlund <32543114+schlunma@users.noreply.github.com>
Date: Thu, 5 Oct 2023 15:28:56 +0200
Subject: [PATCH 2/8] Remove deprecated option `offline` from CI configuration
 (#3367)

---
 .circleci/config.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.circleci/config.yml b/.circleci/config.yml
index ad43c7f495..47e87cf517 100644
--- a/.circleci/config.yml
+++ b/.circleci/config.yml
@@ -214,7 +214,7 @@ jobs:
             conda activate esmvaltool
             mkdir -p ~/climate_data
             esmvaltool config get_config_user
-            echo "offline: false" >> ~/.esmvaltool/config-user.yml
+            echo "search_esgf: when_missing" >> ~/.esmvaltool/config-user.yml
             cat ~/.esmvaltool/config-user.yml
             for recipe in esmvaltool/recipes/testing/recipe_*.yml; do
               esmvaltool run "$recipe"

From 12a2bdb860071d3770e0dd1efec2a700f5b461fc Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Wed, 11 Oct 2023 12:38:28 +0100
Subject: [PATCH 3/8] [Condalock] Update Linux condalock file (#3376)

Co-authored-by: valeriupredoi <valeriupredoi@users.noreply.github.com>
---
 conda-linux-64.lock | 116 ++++++++++++++++++++++----------------------
 1 file changed, 58 insertions(+), 58 deletions(-)

diff --git a/conda-linux-64.lock b/conda-linux-64.lock
index 8f862fe311..a1a14e1190 100644
--- a/conda-linux-64.lock
+++ b/conda-linux-64.lock
@@ -30,7 +30,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-13.2.0-h807b86a_2.cond
 https://conda.anaconda.org/conda-forge/linux-64/aom-3.5.0-h27087fc_0.tar.bz2#a08150fd2298460cd1fcccf626305642
 https://conda.anaconda.org/conda-forge/linux-64/aws-c-common-0.8.23-hd590300_0.conda#cc4f06f7eedb1523f3b83fd0fb3942ff
 https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-h7f98852_4.tar.bz2#a1fd65c7ccbf10880423d82bca54eb54
-https://conda.anaconda.org/conda-forge/linux-64/c-ares-1.19.1-hd590300_0.conda#e8c18d865be43e2fb3f7a145b6adf1f5
+https://conda.anaconda.org/conda-forge/linux-64/c-ares-1.20.1-hd590300_0.conda#6642e4faa4804be3a0e7edfefbd16595
 https://conda.anaconda.org/conda-forge/linux-64/charls-2.4.2-h59595ed_0.conda#4336bd67920dd504cd8c6761d6a99645
 https://conda.anaconda.org/conda-forge/linux-64/dav1d-1.2.1-hd590300_0.conda#418c6ca5929a611cbd69204907a83995
 https://conda.anaconda.org/conda-forge/linux-64/freexl-1.0.6-h166bdaf_1.tar.bz2#897e772a157faf3330d72dd291486f62
@@ -49,7 +49,7 @@ https://conda.anaconda.org/conda-forge/linux-64/jxrlib-1.1-h7f98852_2.tar.bz2#8e
 https://conda.anaconda.org/conda-forge/linux-64/keyutils-1.6.1-h166bdaf_0.tar.bz2#30186d27e2c9fa62b45fb1476b7200e3
 https://conda.anaconda.org/conda-forge/linux-64/lerc-4.0.0-h27087fc_0.tar.bz2#76bbff344f0134279f225174e9064c8f
 https://conda.anaconda.org/conda-forge/linux-64/libabseil-20230125.3-cxx17_h59595ed_0.conda#d1db1b8be7c3a8983dcbbbfe4f0765de
-https://conda.anaconda.org/conda-forge/linux-64/libaec-1.0.6-hcb278e6_1.conda#0f683578378cddb223e7fd24f785ab2a
+https://conda.anaconda.org/conda-forge/linux-64/libaec-1.1.2-h59595ed_1.conda#127b0be54c1c90760d7fe02ea7a56426
 https://conda.anaconda.org/conda-forge/linux-64/libbrotlicommon-1.0.9-h166bdaf_9.conda#61641e239f96eae2b8492dc7e755828c
 https://conda.anaconda.org/conda-forge/linux-64/libcrc32c-1.1.2-h9c3ff4c_0.tar.bz2#c965a5aa0d5c1c37ffc62dff36e28400
 https://conda.anaconda.org/conda-forge/linux-64/libdeflate-1.18-h0b41bf4_0.conda#6aa9c9de5542ecb07fdda9ca626252d8
@@ -75,7 +75,7 @@ https://conda.anaconda.org/conda-forge/linux-64/lzo-2.10-h516909a_1000.tar.bz2#b
 https://conda.anaconda.org/conda-forge/linux-64/make-4.3-hd18ef5c_1.tar.bz2#4049ebfd3190b580dffe76daed26155a
 https://conda.anaconda.org/conda-forge/linux-64/mbedtls-3.3.0-hcb278e6_0.conda#cc1213f464c357b647cc5dde5cfca881
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@@ -403,12 +404,11 @@ https://conda.anaconda.org/conda-forge/noarch/pytest-xdist-3.3.1-pyhd8ed1ab_0.co
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-https://conda.anaconda.org/conda-forge/linux-64/aiohttp-3.8.5-py311h459d7ec_0.conda#82a817c46ac339c0166f043f56492f33
+https://conda.anaconda.org/conda-forge/linux-64/aiohttp-3.8.6-py311h459d7ec_1.conda#7d4b63a745f293029b5689b0b5d8aa15
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@@ -418,28 +418,28 @@ https://conda.anaconda.org/conda-forge/linux-64/contourpy-1.1.1-py311h9547e67_1.
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-https://conda.anaconda.org/conda-forge/noarch/identify-2.5.29-pyhd8ed1ab_0.conda#5bdbb1cb692649720b60f261b41760cd
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@@ -467,7 +467,7 @@ https://conda.anaconda.org/conda-forge/noarch/pylint-plugin-utils-0.7-pyhd8ed1ab
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+https://conda.anaconda.org/conda-forge/linux-64/scikit-learn-1.3.1-py311hc009520_1.conda#0f06a0c10766b511c62050f9aed88b24
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@@ -487,7 +487,7 @@ https://conda.anaconda.org/conda-forge/noarch/nc-time-axis-1.4.1-pyhd8ed1ab_0.ta
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+https://conda.anaconda.org/conda-forge/linux-64/py-xgboost-1.7.6-cuda112py311hba2dd9b_3.conda#8ab84a4da2d1f9f5666a6795d625732e
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@@ -554,15 +554,15 @@ https://conda.anaconda.org/conda-forge/noarch/r-withr-2.5.0-r41hc72bb7e_1.tar.bz
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+https://conda.anaconda.org/conda-forge/linux-64/scikit-image-0.22.0-py311hb755f60_1.conda#8eb9ec7e79696fcb4703374490d7f895
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-https://conda.anaconda.org/conda-forge/noarch/nbconvert-core-7.8.0-pyhd8ed1ab_0.conda#62345c9e24f898bf492979be84a6eb0a
+https://conda.anaconda.org/conda-forge/noarch/nbconvert-core-7.9.2-pyhd8ed1ab_0.conda#01e4314c780ca73759c694ce3ece281f
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@@ -594,11 +594,11 @@ https://conda.anaconda.org/conda-forge/linux-64/r-spam-2.9_1-r41hb20cf53_1.conda
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-https://conda.anaconda.org/conda-forge/noarch/seaborn-0.12.2-hd8ed1ab_0.conda#50847a47c07812f88581081c620f5160
+https://conda.anaconda.org/conda-forge/noarch/seaborn-0.13.0-hd8ed1ab_0.conda#ebd31a95a7008b7e164dad9dbbb5bb5a
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-https://conda.anaconda.org/conda-forge/linux-64/xgboost-1.7.6-cuda112py311h2344cce_2.conda#97cd4e1589b8ea11e0f78d2f0c7cc217
+https://conda.anaconda.org/conda-forge/linux-64/xgboost-1.7.6-cuda112py311hba2dd9b_3.conda#da95aed99d1fbeebece76cf890cec374
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-https://conda.anaconda.org/conda-forge/noarch/nbconvert-pandoc-7.8.0-pyhd8ed1ab_0.conda#1dba1a577df2625a24667612a069e91c
+https://conda.anaconda.org/conda-forge/noarch/nbconvert-pandoc-7.9.2-pyhd8ed1ab_0.conda#1ad46253f2eb46fb8c9b2c22b7ca012f
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@@ -621,7 +621,7 @@ https://conda.anaconda.org/conda-forge/linux-64/r-specsverification-0.5_3-r41ha5
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-https://conda.anaconda.org/conda-forge/noarch/nbconvert-7.8.0-pyhd8ed1ab_0.conda#43bce95e8c474dd21d7ed5de8b4806f7
+https://conda.anaconda.org/conda-forge/noarch/nbconvert-7.9.2-pyhd8ed1ab_0.conda#16ccaddfcfa0a1a606a9ecf6a52d6c11
 https://conda.anaconda.org/conda-forge/noarch/r-cyclocomp-1.1.0-r41hc72bb7e_1005.tar.bz2#800e1da5bf774be48934b8865dd78d33
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From f88b0afa045a83082704c028416d375b6b1c78a5 Mon Sep 17 00:00:00 2001
From: Valeriu Predoi <valeriu.predoi@gmail.com>
Date: Thu, 12 Oct 2023 14:27:32 +0100
Subject: [PATCH 4/8] replace Anaconda badge with dynamicl shield on README
 entry page (#3375)

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 069ce0a0c6..71403fbf90 100644
--- a/README.md
+++ b/README.md
@@ -8,7 +8,7 @@
 [![Codacy Badge](https://app.codacy.com/project/badge/Coverage/79bf6932c2e844eea15d0fb1ed7e415c)](https://www.codacy.com/gh/ESMValGroup/ESMValTool?utm_source=github.com&utm_medium=referral&utm_content=ESMValGroup/ESMValTool&utm_campaign=Badge_Coverage)
 [![Codacy Badge](https://app.codacy.com/project/badge/Grade/79bf6932c2e844eea15d0fb1ed7e415c)](https://www.codacy.com/gh/ESMValGroup/ESMValTool?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=ESMValGroup/ESMValTool&amp;utm_campaign=Badge_Grade)
 [![Docker Build Status](https://img.shields.io/docker/cloud/build/esmvalgroup/esmvaltool.svg)](https://hub.docker.com/r/esmvalgroup/esmvaltool/)
-[![Anaconda-Server Badge](https://anaconda.org/conda-forge/esmvaltool/badges/version.svg)](https://anaconda.org/conda-forge/esmvaltool)
+[![Anaconda-Server Badge](https://img.shields.io/badge/Anaconda.org-2.9.0-blue.svg)](https://anaconda.org/conda-forge/esmvaltool)
 ![stand with Ukraine](https://badgen.net/badge/stand%20with/UKRAINE/?color=0057B8&labelColor=FFD700)
 
 ![esmvaltoollogo](https://raw.githubusercontent.com/ESMValGroup/ESMValTool/main/doc/sphinx/source/figures/ESMValTool-logo-2.png)

From 097e629a2cf8b88037ce0e2a9b21355059725b4b Mon Sep 17 00:00:00 2001
From: Emma Hogan <ehogan@users.noreply.github.com>
Date: Thu, 19 Oct 2023 12:37:25 +0100
Subject: [PATCH 5/8] Add the dataset version in the heatwaves_coldwaves recipe
 to avoid the "Unknown file format" issue on JASMIN (#3373)

Co-authored-by: Valeriu Predoi <valeriu.predoi@gmail.com>
---
 esmvaltool/recipes/recipe_heatwaves_coldwaves.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/esmvaltool/recipes/recipe_heatwaves_coldwaves.yml b/esmvaltool/recipes/recipe_heatwaves_coldwaves.yml
index 6481e33971..aae6491103 100644
--- a/esmvaltool/recipes/recipe_heatwaves_coldwaves.yml
+++ b/esmvaltool/recipes/recipe_heatwaves_coldwaves.yml
@@ -27,7 +27,7 @@ datasets:
   # - {dataset: IPSL-CM5A-MR, type: exp, project: CMIP5, exp: rcp85,
   #    ensemble: r1i1p1, start_year: 2020, end_year: 2040}
   - {dataset: bcc-csm1-1, type: exp, project: CMIP5, exp: historical,
-     ensemble: r1i1p1, start_year: 1971, end_year: 2000}
+     ensemble: r1i1p1, start_year: 1971, end_year: 2000, version: v1}
   - {dataset: bcc-csm1-1, type: exp, project: CMIP5, exp: rcp85,
      ensemble: r1i1p1, start_year: 2060, end_year: 2080}
 

From 5858bf4dc24ac8e17e47f3420a580b727d8f25df Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Mon, 23 Oct 2023 13:54:09 +0100
Subject: [PATCH 6/8] [Condalock] Update Linux condalock file (#3390)

Co-authored-by: valeriupredoi <valeriupredoi@users.noreply.github.com>
---
 conda-linux-64.lock | 80 +++++++++++++++++++++++----------------------
 1 file changed, 41 insertions(+), 39 deletions(-)

diff --git a/conda-linux-64.lock b/conda-linux-64.lock
index a1a14e1190..e77b47d2b9 100644
--- a/conda-linux-64.lock
+++ b/conda-linux-64.lock
@@ -59,7 +59,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libffi-3.4.2-h7f98852_5.tar.bz2#
 https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-13.2.0-ha4646dd_2.conda#78fdab09d9138851dde2b5fe2a11019e
 https://conda.anaconda.org/conda-forge/linux-64/libiconv-1.17-h166bdaf_0.tar.bz2#b62b52da46c39ee2bc3c162ac7f1804d
 https://conda.anaconda.org/conda-forge/linux-64/libjpeg-turbo-2.1.5.1-hd590300_1.conda#323e90742f0f48fc22bea908735f55e6
-https://conda.anaconda.org/conda-forge/linux-64/libnsl-2.0.0-hd590300_1.conda#854e3e1623b39777140f199c5f9ab952
+https://conda.anaconda.org/conda-forge/linux-64/libnsl-2.0.1-hd590300_0.conda#30fd6e37fe21f86f4bd26d6ee73eeec7
 https://conda.anaconda.org/conda-forge/linux-64/libnuma-2.0.16-h0b41bf4_1.conda#28bfe2cb11357ccc5be21101a6b7ce86
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 https://conda.anaconda.org/conda-forge/linux-64/libsodium-1.0.18-h36c2ea0_1.tar.bz2#c3788462a6fbddafdb413a9f9053e58d
@@ -128,7 +128,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.43.2-h2797004_0.cond
 https://conda.anaconda.org/conda-forge/linux-64/libssh2-1.11.0-h0841786_0.conda#1f5a58e686b13bcfde88b93f547d23fe
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 https://conda.anaconda.org/conda-forge/linux-64/libxcb-1.15-h0b41bf4_0.conda#33277193f5b92bad9fdd230eb700929c
-https://conda.anaconda.org/conda-forge/linux-64/libxgboost-1.7.6-cuda112h075c576_3.conda#c26e8921dcf0a989111f7ef375edeed3
+https://conda.anaconda.org/conda-forge/linux-64/libxgboost-1.7.6-cuda118h4159b1e_5.conda#ae32f359ce92c49c29a45d6f5e612094
 https://conda.anaconda.org/conda-forge/linux-64/libxml2-2.11.5-h0d562d8_0.conda#558ab736404275d7df61c473c1af35aa
 https://conda.anaconda.org/conda-forge/linux-64/libzip-1.10.1-h2629f0a_3.conda#ac79812548e7e8cf61f7b0abdef01d3b
 https://conda.anaconda.org/conda-forge/linux-64/mpfr-4.2.0-hb012696_0.conda#14d87bdff2cbd3b1179a29fb316ed743
@@ -140,7 +140,7 @@ https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-h2797004_0.conda#51333
 https://conda.anaconda.org/conda-forge/linux-64/ucx-1.14.1-h64cca9d_5.conda#39aa3b356d10d7e5add0c540945a0944
 https://conda.anaconda.org/conda-forge/linux-64/xorg-fixesproto-5.0-h7f98852_1002.tar.bz2#65ad6e1eb4aed2b0611855aff05e04f6
 https://conda.anaconda.org/conda-forge/linux-64/xorg-libsm-1.2.4-h7391055_0.conda#93ee23f12bc2e684548181256edd2cf6
-https://conda.anaconda.org/conda-forge/linux-64/zeromq-4.3.4-h9c3ff4c_1.tar.bz2#21743a8d2ea0c8cfbbf8fe489b0347df
+https://conda.anaconda.org/conda-forge/linux-64/zeromq-4.3.5-h59595ed_0.conda#8851084c192dbc56215ac4e3c9aa30fa
 https://conda.anaconda.org/conda-forge/linux-64/zlib-1.2.13-hd590300_5.conda#68c34ec6149623be41a1933ab996a209
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 https://conda.anaconda.org/conda-forge/linux-64/aws-c-io-0.13.28-h3870b5a_0.conda#b775667301ab249f94ad2bea91fc4223
@@ -172,12 +172,11 @@ https://conda.anaconda.org/conda-forge/linux-64/python-3.11.6-hab00c5b_0_cpython
 https://conda.anaconda.org/conda-forge/linux-64/sqlite-3.43.2-h2c6b66d_0.conda#c37b95bcd6c6833dacfd5df0ae2f4303
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 https://conda.anaconda.org/conda-forge/linux-64/udunits2-2.2.28-h40f5838_3.conda#6bb8deb138f87c9d48320ac21b87e7a1
-https://conda.anaconda.org/conda-forge/linux-64/xorg-libx11-1.8.6-h8ee46fc_0.conda#7590b76c3d11d21caa44f3fc38ac584a
+https://conda.anaconda.org/conda-forge/linux-64/xorg-libx11-1.8.7-h8ee46fc_0.conda#49e482d882669206653b095f5206c05b
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-https://conda.anaconda.org/conda-forge/linux-64/antlr-python-runtime-4.7.2-py311h38be061_1003.tar.bz2#0ab8f8f0cae99343907fe68cda11baea
+https://conda.anaconda.org/conda-forge/noarch/antlr-python-runtime-4.11.1-pyhd8ed1ab_0.tar.bz2#15109c4977d39ad7aa3423f57243e286
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-https://conda.anaconda.org/conda-forge/linux-64/astroid-3.0.0-py311h38be061_1.conda#ddef045db01d69489c6d74b7e577859b
 https://conda.anaconda.org/conda-forge/linux-64/atk-1.0-2.38.0-hd4edc92_1.tar.bz2#6c72ec3e660a51736913ef6ea68c454b
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@@ -189,13 +188,13 @@ https://conda.anaconda.org/conda-forge/noarch/certifi-2023.7.22-pyhd8ed1ab_0.con
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-https://conda.anaconda.org/conda-forge/noarch/cloudpickle-2.2.1-pyhd8ed1ab_0.conda#b325bfc4cff7d7f8a868f1f7ecc4ed16
+https://conda.anaconda.org/conda-forge/noarch/cloudpickle-3.0.0-pyhd8ed1ab_0.conda#753d29fe41bb881e4b9c004f0abf973f
 https://conda.anaconda.org/conda-forge/noarch/codespell-2.2.6-pyhd8ed1ab_0.conda#a206349b7bb7475ae580f987cb425bdd
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-https://conda.anaconda.org/conda-forge/linux-64/cython-3.0.3-py311hb755f60_0.conda#c54d71e8031a10d08f2e87ff81821588
+https://conda.anaconda.org/conda-forge/linux-64/cython-3.0.4-py311hb755f60_0.conda#6dc0be74820d94a0606595130218981c
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 https://conda.anaconda.org/conda-forge/noarch/distlib-0.3.7-pyhd8ed1ab_0.conda#12d8aae6994f342618443a8f05c652a0
@@ -221,9 +220,10 @@ https://conda.anaconda.org/conda-forge/noarch/imagesize-1.4.1-pyhd8ed1ab_0.tar.b
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+https://conda.anaconda.org/conda-forge/linux-64/lazy-object-proxy-1.9.0-py311h459d7ec_1.conda#7cc99d87755a9e64586a6004c5f0f534
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-https://conda.anaconda.org/conda-forge/linux-64/libblas-3.9.0-18_linux64_openblas.conda#bcddbb497582ece559465b9cd11042e7
+https://conda.anaconda.org/conda-forge/linux-64/libblas-3.9.0-19_linux64_openblas.conda#420f4e9be59d0dc9133a0f43f7bab3f3
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@@ -240,7 +240,7 @@ https://conda.anaconda.org/conda-forge/noarch/munch-4.0.0-pyhd8ed1ab_0.conda#376
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-https://conda.anaconda.org/conda-forge/noarch/networkx-3.1-pyhd8ed1ab_0.conda#254f787d5068bc89f578bf63893ce8b4
+https://conda.anaconda.org/conda-forge/noarch/networkx-3.2-pyhd8ed1ab_1.conda#522039fb968d6d0a10e872e6f3856f53
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@@ -263,20 +263,20 @@ https://conda.anaconda.org/conda-forge/linux-64/python-xxhash-3.4.1-py311h459d7e
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-https://conda.anaconda.org/conda-forge/linux-64/rpds-py-0.10.4-py311h46250e7_0.conda#fd2b9bb72eeb3d90187a6d77c46a228e
+https://conda.anaconda.org/conda-forge/linux-64/rpds-py-0.10.6-py311h46250e7_0.conda#b7237977dbca779aaaab65f42f5558d9
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-https://conda.anaconda.org/conda-forge/linux-64/tbb-2021.10.0-h00ab1b0_1.conda#cffdfb316b2516616c331462c4ac5672
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@@ -287,13 +287,14 @@ https://conda.anaconda.org/conda-forge/noarch/tomlkit-0.12.1-pyha770c72_0.conda#
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+https://conda.anaconda.org/conda-forge/noarch/trove-classifiers-2023.10.18-pyhd8ed1ab_0.conda#5e2b0a292b9a3adb1c412a1e361b8e69
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+https://conda.anaconda.org/conda-forge/linux-64/wrapt-1.15.0-py311h459d7ec_1.conda#f4d770a09066aaa313b5cc22c0f6e9d1
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 https://conda.anaconda.org/conda-forge/linux-64/python-stratify-0.3.0-py311h1f0f07a_1.conda#cd36a89a048ad2bcc6d8b43f648fb1d0
 https://conda.anaconda.org/conda-forge/linux-64/r-base-4.1.3-hfabd6f2_9.conda#0ab4cf54fbddc0cc9ff260c6f77f8c84
@@ -470,7 +472,7 @@ https://conda.anaconda.org/conda-forge/linux-64/rasterio-1.3.8-py311h41e4db2_0.c
 https://conda.anaconda.org/conda-forge/linux-64/scikit-learn-1.3.1-py311hc009520_1.conda#0f06a0c10766b511c62050f9aed88b24
 https://conda.anaconda.org/conda-forge/noarch/sparse-0.14.0-pyhd8ed1ab_0.conda#ee01b310177a0612554b9d20e537fdbe
 https://conda.anaconda.org/conda-forge/noarch/tifffile-2023.9.26-pyhd8ed1ab_0.conda#d133bea7d8ac17552492a0629229eeb1
-https://conda.anaconda.org/conda-forge/noarch/xarray-2023.9.0-pyhd8ed1ab_0.conda#158c89bbc0f2597f33e8ce1aea59e0ee
+https://conda.anaconda.org/conda-forge/noarch/xarray-2023.10.1-pyhd8ed1ab_0.conda#9b20e5d68eea6878a0a6fc57a3043889
 https://conda.anaconda.org/conda-forge/noarch/zarr-2.16.1-pyhd8ed1ab_0.conda#59ec835edbee50266b7bdbadab7ba335
 https://conda.anaconda.org/conda-forge/linux-64/cartopy-0.22.0-py311h320fe9a_0.conda#1271b2375735e2aaa6d6770dbe2ad087
 https://conda.anaconda.org/conda-forge/noarch/cf_xarray-0.8.4-pyhd8ed1ab_0.conda#18472f8f9452f962fe0bcb1b8134b494
@@ -487,7 +489,7 @@ https://conda.anaconda.org/conda-forge/noarch/nc-time-axis-1.4.1-pyhd8ed1ab_0.ta
 https://conda.anaconda.org/conda-forge/linux-64/ncl-6.6.2-hf70af60_47.conda#ee27133164cb9f5e74681bdb8839688f
 https://conda.anaconda.org/conda-forge/linux-64/nco-5.1.6-hd62b316_0.conda#af7780f76ee37325d264327e21a478f5
 https://conda.anaconda.org/conda-forge/linux-64/psyplot-1.4.3-py311h38be061_1.tar.bz2#f0c9a1067c03e8f05e53ef0c5ad5fab3
-https://conda.anaconda.org/conda-forge/linux-64/py-xgboost-1.7.6-cuda112py311hba2dd9b_3.conda#8ab84a4da2d1f9f5666a6795d625732e
+https://conda.anaconda.org/conda-forge/linux-64/py-xgboost-1.7.6-cuda118py311he6248c7_5.conda#04c384f45bafbf97696642bb723aa67e
 https://conda.anaconda.org/conda-forge/noarch/pylint-celery-0.3-py_1.tar.bz2#e29456a611a62d3f26105a2f9c68f759
 https://conda.anaconda.org/conda-forge/noarch/pylint-django-2.5.3-pyhd8ed1ab_0.tar.bz2#00d8853fb1f87195722ea6a582cc9b56
 https://conda.anaconda.org/conda-forge/noarch/pylint-flask-0.6-py_0.tar.bz2#5a9afd3d0a61b08d59eed70fab859c1b
@@ -554,7 +556,7 @@ https://conda.anaconda.org/conda-forge/noarch/r-withr-2.5.0-r41hc72bb7e_1.tar.bz
 https://conda.anaconda.org/conda-forge/linux-64/r-xfun-0.39-r41ha503ecb_0.conda#555ee06849209b9471946da6f09bb98b
 https://conda.anaconda.org/conda-forge/noarch/r-xmlparsedata-1.0.5-r41hc72bb7e_1.tar.bz2#921c0ef7104d8df0ab506f1bb81a062c
 https://conda.anaconda.org/conda-forge/linux-64/r-yaml-2.3.7-r41h133d619_0.conda#4af88071a607237aa73a3cbd51788a39
-https://conda.anaconda.org/conda-forge/linux-64/scikit-image-0.22.0-py311hb755f60_1.conda#8eb9ec7e79696fcb4703374490d7f895
+https://conda.anaconda.org/conda-forge/linux-64/scikit-image-0.22.0-py311h320fe9a_2.conda#e94b7f09b52628b89e66cdbd8c3029dd
 https://conda.anaconda.org/conda-forge/noarch/seaborn-base-0.13.0-pyhd8ed1ab_0.conda#082666331726b2438986cfe33ae9a8ee
 https://conda.anaconda.org/conda-forge/linux-64/statsmodels-0.14.0-py311h1f0f07a_2.conda#8f1e772e5430ce48229740ec00a90b61
 https://conda.anaconda.org/conda-forge/linux-64/cdo-2.2.0-he026af2_4.conda#6c00b0a21b3de8a149eee137e83465d3
@@ -563,9 +565,9 @@ https://conda.anaconda.org/conda-forge/noarch/iris-3.7.0-pyha770c72_0.conda#dccc
 https://conda.anaconda.org/conda-forge/noarch/lime-0.2.0.1-pyhd8ed1ab_1.tar.bz2#789ce01416721a5533fb74aa4361fd13
 https://conda.anaconda.org/conda-forge/noarch/mapgenerator-1.0.7-pyhd8ed1ab_0.conda#d18db96ef2a920b0ecefe30282b0aecf
 https://conda.anaconda.org/conda-forge/noarch/nbconvert-core-7.9.2-pyhd8ed1ab_0.conda#01e4314c780ca73759c694ce3ece281f
-https://conda.anaconda.org/conda-forge/noarch/prospector-1.10.2-pyhd8ed1ab_0.conda#2c536985982f7e531df8d640f554008a
+https://conda.anaconda.org/conda-forge/noarch/prospector-1.10.3-pyhd8ed1ab_0.conda#f551d4d859a1d70c6abff8310a655481
 https://conda.anaconda.org/conda-forge/linux-64/psy-simple-1.4.1-py311h38be061_2.tar.bz2#4c9101d329f6bc09c2617a80e3eb9c89
-https://conda.anaconda.org/conda-forge/noarch/py-cordex-0.6.3-pyhd8ed1ab_0.conda#de9f9392273a1e6095930a21561a37e9
+https://conda.anaconda.org/conda-forge/noarch/py-cordex-0.6.4-pyhd8ed1ab_0.conda#a30ffe78645b5777aa21d3e0f2d2a015
 https://conda.anaconda.org/conda-forge/linux-64/pyarrow-12.0.1-py311h39c9aba_7_cpu.conda#d513ab8d10ec5f3ee45b419c836195ec
 https://conda.anaconda.org/conda-forge/linux-64/pydot-1.4.2-py311h38be061_4.conda#5c223cb0d9c05552bf9d1586a92720b2
 https://conda.anaconda.org/conda-forge/linux-64/r-askpass-1.1-r41h06615bd_3.tar.bz2#c8ec8683302ad9a2345cb31ab28e6c6b
@@ -596,8 +598,8 @@ https://conda.anaconda.org/conda-forge/linux-64/r-xml2-1.3.4-r41h1ad5fc0_1.conda
 https://conda.anaconda.org/conda-forge/linux-64/r-zoo-1.8_12-r41h133d619_0.conda#1d432d2eba171727afd03507faa5e2f6
 https://conda.anaconda.org/conda-forge/noarch/seaborn-0.13.0-hd8ed1ab_0.conda#ebd31a95a7008b7e164dad9dbbb5bb5a
 https://conda.anaconda.org/conda-forge/noarch/xesmf-0.8.2-pyhd8ed1ab_0.conda#8e765a0eca0ce1cfa889cd9af82a23a8
-https://conda.anaconda.org/conda-forge/linux-64/xgboost-1.7.6-cuda112py311hba2dd9b_3.conda#da95aed99d1fbeebece76cf890cec374
-https://conda.anaconda.org/conda-forge/noarch/dask-2023.9.3-pyhd8ed1ab_0.conda#5b32dc4eb1f5e3097cc33fb0e331b3a4
+https://conda.anaconda.org/conda-forge/linux-64/xgboost-1.7.6-cuda118py311he6248c7_5.conda#00f60bd90006f639468ae33a764b966c
+https://conda.anaconda.org/conda-forge/noarch/dask-2023.10.0-pyhd8ed1ab_0.conda#0c85f5482dd283c2b9ca68d331edb471
 https://conda.anaconda.org/conda-forge/noarch/nbconvert-pandoc-7.9.2-pyhd8ed1ab_0.conda#1ad46253f2eb46fb8c9b2c22b7ca012f
 https://conda.anaconda.org/conda-forge/noarch/prov-2.0.0-pyhd3deb0d_0.tar.bz2#aa9b3ad140f6c0668c646f32e20ccf82
 https://conda.anaconda.org/conda-forge/noarch/psy-maps-1.4.2-pyhd8ed1ab_0.tar.bz2#3ed13103dfd46f71dc870d188bd0b276

From 3e7ff2110a9e235e581b5ff33676fec0796feda9 Mon Sep 17 00:00:00 2001
From: Bouwe Andela <b.andela@esciencecenter.nl>
Date: Thu, 26 Oct 2023 14:48:41 +0200
Subject: [PATCH 7/8] Fix documentation build (#3397)

---
 doc/sphinx/source/conf.py | 11 ++++++++++-
 1 file changed, 10 insertions(+), 1 deletion(-)

diff --git a/doc/sphinx/source/conf.py b/doc/sphinx/source/conf.py
index 6257289715..5ef08c3b06 100644
--- a/doc/sphinx/source/conf.py
+++ b/doc/sphinx/source/conf.py
@@ -153,7 +153,16 @@
 # Theme options are theme-specific and customize the look and feel of a theme
 # further.  For a list of options available for each theme, see the
 # documentation.
-# html_theme_options = {}
+#
+# Avoid the following warning issued by pydata_sphinx_theme:
+#
+# "WARNING: The default value for `navigation_with_keys` will change to `False`
+# in the next release. If you wish to preserve the old behavior for your site,
+# set `navigation_with_keys=True` in the `html_theme_options` dict in your
+# `conf.py` file.Be aware that `navigation_with_keys = True` has negative
+# accessibility implications:
+# https://github.com/pydata/pydata-sphinx-theme/issues/1492"
+html_theme_options = {"navigation_with_keys": False}
 
 # Add any paths that contain custom themes here, relative to this directory.
 # html_theme_path = []

From 604f6fb18c43ed9ea0c91b5446a1de0a3790e2c4 Mon Sep 17 00:00:00 2001
From: Bouwe Andela <b.andela@esciencecenter.nl>
Date: Thu, 26 Oct 2023 18:14:44 +0200
Subject: [PATCH 8/8] Add a realistic example recipe (#3356)

---
 .../IPCC_AR6_figure_9.3a_1850-2100.png        | Bin 0 -> 183259 bytes
 doc/sphinx/source/recipes/index.rst           |   1 +
 doc/sphinx/source/recipes/recipe_examples.rst |  29 ++--
 esmvaltool/diag_scripts/examples/make_plot.py |  76 +++++++++++
 .../recipes/examples/recipe_easy_ipcc.yml     | 126 ++++++++++++++++++
 esmvaltool/references/fox-kemper21ipcc.bibtex |  11 ++
 6 files changed, 235 insertions(+), 8 deletions(-)
 create mode 100644 doc/sphinx/source/recipes/figures/examples/IPCC_AR6_figure_9.3a_1850-2100.png
 create mode 100644 esmvaltool/diag_scripts/examples/make_plot.py
 create mode 100644 esmvaltool/recipes/examples/recipe_easy_ipcc.yml
 create mode 100644 esmvaltool/references/fox-kemper21ipcc.bibtex

diff --git a/doc/sphinx/source/recipes/figures/examples/IPCC_AR6_figure_9.3a_1850-2100.png b/doc/sphinx/source/recipes/figures/examples/IPCC_AR6_figure_9.3a_1850-2100.png
new file mode 100644
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zmAvrLo@o_W?=;qDJ>*0*GHtwleCU;zmywJn9BCUJDM(~^9}f0fM>CE#pC*+nqwJ^;
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HcmV?d00001

diff --git a/doc/sphinx/source/recipes/index.rst b/doc/sphinx/source/recipes/index.rst
index 57c77e8b30..1cb182f39b 100644
--- a/doc/sphinx/source/recipes/index.rst
+++ b/doc/sphinx/source/recipes/index.rst
@@ -99,6 +99,7 @@ IPCC
    recipe_ipccwg1ar6ch3
    recipe_ipccwg1ar5ch9
    recipe_collins13ipcc
+   recipe_examples
 
 Land
 ^^^^
diff --git a/doc/sphinx/source/recipes/recipe_examples.rst b/doc/sphinx/source/recipes/recipe_examples.rst
index 5874e2c1c4..e3c32c4337 100644
--- a/doc/sphinx/source/recipes/recipe_examples.rst
+++ b/doc/sphinx/source/recipes/recipe_examples.rst
@@ -8,20 +8,26 @@ Overview
 
 These are example recipes calling example diagnostic scripts.
 
-The recipe examples/recipe_python.yml produces time series plots of global mean
+The recipe ``examples/recipe_python.yml`` produces time series plots of global mean
 temperature and for the temperature in Amsterdam.
 It also produces a map of global temperature in January 2020.
 
-The recipe examples/recipe_extract_shape.yml produces a map of the mean
+The recipe ``examples/recipe_easy_ipcc.yml`` reproduces part of figure 9.3a from
+`IPCC AR6 - Climate Change 2021: The Physical Science Basis <https://www.ipcc.ch/report/sixth-assessment-report-working-group-i/>`__.
+It demonstrates how ESMValTool can be used to conveniently analyze
+many models on their native grid and is described in detail in the blog post
+`Analysis-ready climate data with ESMValCore <https://blog.esciencecenter.nl/easy-ipcc-powered-by-esmvalcore-19a0b6366ea7>`__.
+
+The recipe ``examples/recipe_extract_shape.yml`` produces a map of the mean
 temperature in the Elbe catchment over the years 2000 to 2002.
 Some example shapefiles for use with this recipe are available
 `here <https://github.com/ESMValGroup/ESMValTool/tree/main/esmvaltool/diag_scripts/shapeselect/testdata>`__,
 make sure to download all files with the same name but different extensions.
 
-The recipe examples/recipe_julia.yml produces a map plot with the mean temperature
+The recipe ``examples/recipe_julia.yml`` produces a map plot with the mean temperature
 over the year 1997 plus a number that is configurable from the recipe.
 
-The recipe examples/recipe_decadal.yml showcases how the ``timerange`` tag
+The recipe ``examples/recipe_decadal.yml`` showcases how the ``timerange`` tag
 can be used to load datasets belonging to the DCPP activity. Produces timeseries
 plots comparing the global mean temperature of a DCPP dataset with an observational
 dataset.
@@ -29,16 +35,16 @@ dataset.
 Available recipes and diagnostics
 ---------------------------------
 
-Recipes are stored in esmvaltool/recipes/
-
+Recipes are stored in `esmvaltool/recipes/ <https://github.com/ESMValGroup/ESMValTool/tree/main/esmvaltool/recipes>`__:
     * examples/recipe_python.yml
+    * examples/recipe_easy_ipcc.yml
     * examples/recipe_extract_shape.yml
     * examples/recipe_julia.yml
     * examples/recipe_decadal.yml
 
-Diagnostics are stored in esmvaltool/diag_scripts/
-
+Diagnostics are stored in `esmvaltool/diag_scripts/ <https://github.com/ESMValGroup/ESMValTool/tree/main/esmvaltool/diag_scripts>`__:
     * examples/diagnostic.py: visualize results and store provenance information
+    * examples/make_plot.py: Create a timeseries plot with likely ranges
     * examples/diagnostic.jl: visualize results and store provenance information
     * examples/decadal_example.py: visualize results and store provenance information
 
@@ -63,6 +69,7 @@ Variables
 ---------
 
 * tas (atmos, monthly, longitude, latitude, time)
+* tos (ocean, monthly, longitude, latitude, time)
 
 Example plots
 -------------
@@ -79,6 +86,12 @@ Example plots
 
    Amsterdam air temperature (multimodel mean of CMIP5 CanESM2 and CMIP6 BCC-ESM1).
 
+.. _easy_ipcc:
+.. figure:: /recipes/figures/examples/IPCC_AR6_figure_9.3a_1850-2100.png
+   :align:   center
+
+   Mean sea surface temperature anomaly (part of figure 9.3a from IPCC AR6).
+
 .. _elbe:
 .. figure::  /recipes/figures/examples/elbe.png
    :align:   center
diff --git a/esmvaltool/diag_scripts/examples/make_plot.py b/esmvaltool/diag_scripts/examples/make_plot.py
new file mode 100644
index 0000000000..b2aa4158f5
--- /dev/null
+++ b/esmvaltool/diag_scripts/examples/make_plot.py
@@ -0,0 +1,76 @@
+"""Python example diagnostic."""
+import logging
+from pathlib import Path
+
+import iris
+import matplotlib.pyplot as plt
+
+from esmvaltool.diag_scripts.shared import run_diagnostic, save_figure
+
+logger = logging.getLogger(Path(__file__).stem)
+
+
+def main(cfg):
+    """Plot part of figure_9.3a from IPCC AR6."""
+    colors = {
+        'historical-ssp126': '#2a3652',
+        'historical-ssp585': '#78333a',
+    }
+    fill_colors = {
+        'historical-ssp126': '#d2d5dc',
+        'historical-ssp585': '#ddced2',
+    }
+    labels = {
+        'historical-ssp126': 'Historical and SSP1-2.6',
+        'historical-ssp585': 'Historical and SSP5-8.5',
+    }
+
+    # Group input data by experiment
+    groups = {}
+    for filename, attributes in cfg['input_data'].items():
+        exp = attributes['exp']
+        if exp not in groups:
+            groups[exp] = {}
+        groups[exp][attributes['dataset']] = filename
+
+    # Loop over experiments to populate plot
+    for exp, group in groups.items():
+        mean = iris.load_cube(group['MultiModelMean'])
+        iris.quickplot.plot(
+            mean,
+            color=colors.get(exp),
+            label=labels.get(exp, exp),
+        )
+
+        p17 = iris.load_cube(group['MultiModelP17'])
+        p83 = iris.load_cube(group['MultiModelP83'])
+        time_coord = mean.coord('time')
+        time_axis = time_coord.units.num2date(time_coord.core_points())
+        plt.fill_between(
+            time_axis,
+            p17.core_data(),
+            p83.core_data(),
+            color=fill_colors.get(exp),
+            label='Likely (17% - 83%) ranges',
+        )
+
+    plt.title('Sea surface temperature anomaly')
+    plt.legend(loc='upper left')
+
+    filename = 'IPCC_AR6_figure_9.3a_1850-2100'
+    provenance_record = {
+        'caption': "Part of figure 9.3a from IPCC AR6.",
+        'authors': [
+            'kalverla_peter',
+            'andela_bouwe',
+        ],
+        'references': ['fox-kemper21ipcc'],
+        'ancestors': list(cfg['input_data'].keys()),
+    }
+    save_figure(filename, provenance_record, cfg, dpi=300)
+
+
+if __name__ == '__main__':
+
+    with run_diagnostic() as config:
+        main(config)
diff --git a/esmvaltool/recipes/examples/recipe_easy_ipcc.yml b/esmvaltool/recipes/examples/recipe_easy_ipcc.yml
new file mode 100644
index 0000000000..7f5696e2b9
--- /dev/null
+++ b/esmvaltool/recipes/examples/recipe_easy_ipcc.yml
@@ -0,0 +1,126 @@
+documentation:
+  title: Easy IPCC
+  description: Reproduce part of IPCC AR6 figure 9.3a.
+  references:
+    - fox-kemper21ipcc
+  authors:
+    - kalverla_peter
+    - andela_bouwe
+  maintainer:
+    - andela_bouwe
+
+preprocessors:
+  easy_ipcc:
+    custom_order: true
+    anomalies:
+      period: month
+      reference:
+        start_year: 1950
+        start_month: 1
+        start_day: 1
+        end_year: 1979
+        end_month: 12
+        end_day: 31
+    area_statistics:
+      operator: mean
+    annual_statistics:
+      operator: mean
+    convert_units:
+      units: 'degrees_C'
+    ensemble_statistics:
+      statistics:
+        - mean
+    multi_model_statistics:
+      statistics:
+        - mean
+        - p17
+        - p83
+      span: full
+      keep_input_datasets: false
+      ignore_scalar_coords: true
+
+diagnostics:
+  AR6_Figure_9.3:
+    variables:
+      tos_ssp585:
+        short_name: tos
+        exp: ['historical', 'ssp585']
+        project: CMIP6
+        mip: Omon
+        preprocessor: easy_ipcc
+        timerange: '1850/2100'
+      tos_ssp126:
+        short_name: tos
+        exp: ['historical', 'ssp126']
+        project: CMIP6
+        mip: Omon
+        timerange: '1850/2100'
+        preprocessor: easy_ipcc
+    scripts:
+      Figure_9.3a:
+        script: examples/make_plot.py
+
+datasets:
+  - {dataset: ACCESS-CM2, ensemble: 'r(1:5)i1p1f1', grid: gn}
+  - {dataset: ACCESS-ESM1-5, ensemble: 'r(1:40)i1p1f1', grid: gn}
+  - {dataset: AWI-CM-1-1-MR, ensemble: r1i1p1f1, grid: gn}
+  - {dataset: BCC-CSM2-MR, ensemble: r1i1p1f1, grid: gn}
+  # - {dataset: CAMS-CSM1-0, ensemble: 'r(1:2)i1p1f1', grid: gn} # available data does not fully cover timerange
+  - {dataset: CAS-ESM2-0, ensemble: r1i1p1f1, grid: gn}
+  - {dataset: CAS-ESM2-0, ensemble: r3i1p1f1, grid: gn}
+  - {dataset: CESM2, ensemble: r4i1p1f1, grid: gn}
+  - {dataset: CESM2, ensemble: 'r(10:11)i1p1f1', grid: gn}
+  - {dataset: CESM2-WACCM, ensemble: r1i1p1f1, grid: gn}
+  - {dataset: CIESM, ensemble: r1i1p1f1, grid: gn}
+  - {dataset: CMCC-CM2-SR5, ensemble: r1i1p1f1, grid: gn}
+  - {dataset: CMCC-ESM2, ensemble: r1i1p1f1, grid: gn}
+  - {dataset: CNRM-CM6-1, ensemble: 'r(1:6)i1p1f2', grid: gn}
+  - {dataset: CNRM-CM6-1-HR, ensemble: r1i1p1f2, grid: gn}
+  - {dataset: CNRM-ESM2-1, ensemble: 'r(1:5)i1p1f2', grid: gn}
+  - {dataset: CanESM5, ensemble: 'r(1:25)i1p(1:2)f1', grid: gn}
+  - {dataset: CanESM5-1, ensemble: 'r1i1p(1:2)f1', grid: gn, institute: CCCma}
+  - {dataset: CanESM5-CanOE, ensemble: 'r(1:3)i1p2f1', grid: gn}
+  - {dataset: EC-Earth3, ensemble: r1i1p1f1, grid: gn}
+  - {dataset: EC-Earth3, ensemble: r4i1p1f1, grid: gn}
+  - {dataset: EC-Earth3, ensemble: r6i1p1f1, grid: gn}
+  # - {dataset: EC-Earth3, ensemble: r9i1p1f1, grid: gn}  # download failure of ssp585
+  - {dataset: EC-Earth3, ensemble: r11i1p1f1, grid: gn}
+  - {dataset: EC-Earth3, ensemble: r15i1p1f1, grid: gn}
+  # - {dataset: EC-Earth3, ensemble: 'r(101:150)i1p1f1', grid: gn}  # available data does not fully cover timerange
+  - {dataset: EC-Earth3-Veg, ensemble: 'r(1:4)i1p1f1', grid: gn}
+  - {dataset: EC-Earth3-Veg, ensemble: r6i1p1f1, grid: gn}
+  # - {dataset: EC-Earth3-Veg-LR, ensemble: 'r(1:3)i1p1f1', grid: gn}  # mismatch between i and j coordinate names between historical and ssp experiment
+  - {dataset: FGOALS-f3-L, ensemble: 'r(1:3)i1p1f1', grid: gn}
+  - {dataset: FGOALS-g3, ensemble: 'r(1:4)i1p1f1', grid: gn}
+  - {dataset: FIO-ESM-2-0, ensemble: 'r(1:3)i1p1f1', grid: gn}
+  - {dataset: GFDL-ESM4, ensemble: r1i1p1f1, grid: gn}
+  - {dataset: GISS-E2-1-G, ensemble: 'r(1:4)i1p5f1', grid: gn, supplementary_variables: [{short_name: areacella, mip: fx, exp: piControl, ensemble: r1i1p5f1}, {short_name: areacello, skip: true}]}
+  - {dataset: GISS-E2-1-G, ensemble: 'r(1:5)i1p1f2', grid: gn, supplementary_variables: [{short_name: areacella, mip: fx, exp: piControl, ensemble: r1i1p1f1}, {short_name: areacello, skip: true}]}
+  - {dataset: GISS-E2-1-G, ensemble: 'r(1:5)i1p3f1', grid: gn, supplementary_variables: [{short_name: areacella, mip: fx, exp: piControl, ensemble: r1i1p3f1}, {short_name: areacello, skip: true}]}
+  - {dataset: GISS-E2-1-H, ensemble: 'r(1:5)i1p1f2', grid: gn, supplementary_variables: [{short_name: areacella, mip: fx, exp: piControl, ensemble: r1i1p1f1}, {short_name: areacello, skip: true}]}
+  - {dataset: GISS-E2-1-H, ensemble: 'r(1:5)i1p3f1', grid: gn, supplementary_variables: [{short_name: areacella, mip: fx, exp: piControl, ensemble: r1i1p3f1}, {short_name: areacello, skip: true}]}
+  - {dataset: GISS-E2-2-G, ensemble: 'r(1:5)i1p3f1', grid: gn, supplementary_variables: [{short_name: areacella, mip: fx, exp: piControl, ensemble: r1i1p1f1}, {short_name: areacello, skip: true}]}
+  - {dataset: HadGEM3-GC31-LL, ensemble: r1i1p1f3, grid: gn}
+  - {dataset: HadGEM3-GC31-MM, ensemble: r1i1p1f3, grid: gn}
+  # - {dataset: IITM-ESM, ensemble: r1i1p1f1, grid: gn}  # available data does not fully cover timerange
+  - {dataset: INM-CM4-8, ensemble: r1i1p1f1, grid: gr1}
+  - {dataset: INM-CM5-0, ensemble: r1i1p1f1, grid: gr1}
+  - {dataset: IPSL-CM6A-LR, ensemble: 'r(1:4)i1p1f1', grid: gn}
+  - {dataset: IPSL-CM6A-LR, ensemble: r6i1p1f1, grid: gn}
+  - {dataset: IPSL-CM6A-LR, ensemble: r14i1p1f1, grid: gn}
+  # - {dataset: KACE-1-0-G, ensemble: 'r(1:3)i1p1f1', grid: gr}  # unstructured grid but no cell area information available
+  # - {dataset: KIOST-ESM, ensemble: r1i1p1f1, grid: gr1}  # historical and ssp126 experiment are on different grids
+  - {dataset: MCM-UA-1-0, ensemble: r1i1p1f2, grid: gn}
+  - {dataset: MIROC-ES2H, ensemble: r1i1p4f2, grid: gn}
+  - {dataset: MIROC-ES2L, ensemble: 'r(1:10)i1p1f2', grid: gn}
+  - {dataset: MIROC6, ensemble: 'r(1:50)i1p1f1', grid: gn}
+  - {dataset: MPI-ESM1-2-HR, ensemble: 'r1i1p1f1', grid: gn}
+  # - {dataset: MPI-ESM1-2-HR, ensemble: 'r(1:2)i1p1f1', grid: gn}  # second ensemble member causes warnings about large graphs in `concatenate` preprocessor step
+  - {dataset: MPI-ESM1-2-LR, ensemble: 'r(1:30)i1p1f1', grid: gn}
+  - {dataset: MRI-ESM2-0, ensemble: 'r(1:5)i1p1f1', grid: gn}
+  # - {dataset: NESM3, ensemble: 'r(1:2)i1p1f1', grid: gn}  # cannot be used due to https://github.com/ESMValGroup/ESMValCore/issues/2101
+  # - {dataset: NorESM2-LM, ensemble: r1i1p1f1, grid: gn}  # duplicated areacello file with wrong name
+  - {dataset: NorESM2-MM, ensemble: r1i1p1f1, grid: gn}
+  - {dataset: TaiESM1, ensemble: r1i1p1f1, grid: gn}
+  - {dataset: UKESM1-0-LL, ensemble: 'r(1:4)i1p1f2', grid: gn}
+  - {dataset: UKESM1-0-LL, ensemble: r8i1p1f2, grid: gn}
diff --git a/esmvaltool/references/fox-kemper21ipcc.bibtex b/esmvaltool/references/fox-kemper21ipcc.bibtex
new file mode 100644
index 0000000000..e26a480f46
--- /dev/null
+++ b/esmvaltool/references/fox-kemper21ipcc.bibtex
@@ -0,0 +1,11 @@
+@inbook{fox-kemper21ipcc,
+  author={B. Fox-Kemper and H.T. Hewitt and C. Xiao and G. Aðalgeirsdóttir and S.S. Drijfhout and T.L. Edwards and N.R. Golledge and M. Hemer and R.E. Kopp and G. Krinner and A. Mix and D. Notz and S. Nowicki and I.S. Nurhati and L. Ruiz and J.-B. Sallée and A.B.A. Slangen and Y. Yu},
+  editor={V. Masson-Delmotte and P. Zhai and A. Pirani and S.L. Connors and C. Pean and S. Berger and N. Caud and Y. Chen and L. Goldfarb and M.I. Gomis and M. Huang and K. Leitzell and E. Lonnoy and J.B.R. Matthews and T.K. Maycock and T. Waterfield and O. Yelekci and R. Yu and B. Zhou},
+  title={Ocean, Cryosphere and Sea Level Change},
+  booktitle={Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change},
+  year={2021},
+  publisher={Cambridge University Press},
+  address={Cambridge, UK and New York, NY, USA},
+  pages = {1211--1362},
+  doi={10.1017/9781009157896.011}
+}