From ff5f296702f8b15bf29411d99b415cac5aad3446 Mon Sep 17 00:00:00 2001
From: Junjie YU <131512001+JunjieYU-UoM@users.noreply.github.com>
Date: Wed, 28 Feb 2024 11:58:27 +0000
Subject: [PATCH] update intro

---
 docs/container/intro.rst    | 2 +-
 docs/examples/explore_up.md | 4 ++--
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/docs/container/intro.rst b/docs/container/intro.rst
index 538efad..1a8c6fb 100644
--- a/docs/container/intro.rst
+++ b/docs/container/intro.rst
@@ -35,7 +35,7 @@ Running CMLU within CLM (Community Land Model) requires a Linux operation system
 .. note::
     PTS mode currently **CAN NOT** run with initial conditions, however, we can still can take advantage of this mode. Firstly, we can run case for longer time simulation to get the stable conditions. Moreover, although the land use models is model simulations are sensitive to initial soil moisture conditions, the urban module (CLMU) is less affected by soil. 
     
-    We compared two cases of different simulation times of New York Grid ``lat=40.05``, ``lon=-73.75``, ``res=f09_g17``, ``compset=2000_DATM%CRUv7_CLM50%SP_SICE_SOCN_SROF_SGLC_SWAV``. The 2015 JJA average **TREFMXAV**, **TREFMNAV***, **TSA** and **RH2M** of high density urban between the case of simulation time of 2005-2015 and the case of simulation time of 2015 JJA were compared. Their differences are `0.009 K`, `0.035 K`, `0.023 K` and `0.076 %`, respectively. However, it should be noted that the differences in `vegetated_or_bare_soil` land unit are `0.123 K`, `0.191 K`, `0.036 K` and `0.173 %`, which are more significantly affected than urban. We recommend that a long time simulation or spin-up for the experiments need non-urban variables would be more precise. `TREFMXAV`, `TREFMNAV`, `TSA` and `RH2M` are daily maximum of average 2-m temperature, daily minimum of average 2-m temperature, 2m air temperature and 2m relative humidity, respectively.
+    We compared two cases of different simulation times of New York Grid ``lat=40.05``, ``lon=-73.75``, ``res=f09_g17``, ``compset=2000_DATM%CRUv7_CLM50%SP_SICE_SOCN_SROF_SGLC_SWAV``. The 2015 JJA average **TREFMXAV**, **TREFMNAV**, **TSA** and **RH2M** of high density urban between the case of simulation time of 2005-2015 and the case of simulation time of 2015 JJA were compared. Their differences are `0.009 K`, `0.035 K`, `0.023 K` and `0.076 %`, respectively. However, it should be noted that the differences in `vegetated_or_bare_soil` land unit are `0.123 K`, `0.191 K`, `0.036 K` and `0.173 %`, which are more significantly affected than urban. We recommend that a long time simulation or spin-up for the experiments need non-urban variables would be more precise. `TREFMXAV`, `TREFMNAV`, `TSA` and `RH2M` are daily maximum of average 2-m temperature, daily minimum of average 2-m temperature, 2m air temperature and 2m relative humidity, respectively.
 
 Python for urban climate exploration
 ------------------------------------
diff --git a/docs/examples/explore_up.md b/docs/examples/explore_up.md
index 6f994f7..63c22fd 100644
--- a/docs/examples/explore_up.md
+++ b/docs/examples/explore_up.md
@@ -172,9 +172,9 @@ for i in range(1, 25):
 
     # reset the cases
     command_0 = f"sudo -S docker exec myclm rm -rf /p/scratch/CESMDATAROOT/CaseOutputs/ssp370up"
-    run_command(command=command_0, password="Manchestermedal")
+    run_command(command=command_0, password=password)
     command_1 = f"sudo -S docker exec myclm rm -rf /p/project/clm5.0/cime/scripts/ssp370up"
-    run_command(command=command_1, password="Manchestermedal")
+    run_command(command=command_1, password=password)
 
 ```