Make table and references updates consistent throughout

Author: slevis-lmwg

doc/source/tech_note/Introduction/CLM50_Tech_Note_Introduction.rst

@@ -125,7 +125,7 @@ P. O. Box 3000, Boulder, Colorado 80307-300
 
 - :numref:`Table Respiration fractions for Century-based structure` Respiration fractions for litter and SOM pools for Century-based structure
 
-- :numref:`Table PFT-specific combustion completeness and fire mortality factors` PFT-specific combustion completeness and fire mortality factors.
+- :numref:`Table PFT-specific fire parameters` PFT-specific fire parameters.
 
 - :numref:`Table Methane Parameter descriptions`  Parameter descriptions and sensitivity analysis ranges applied in the methane model.
 

doc/source/tech_note/References/CLM50_Tech_Note_References.rst

@@ -1161,6 +1161,10 @@ Owen, P.R. 1964. Saltation of uniform grains in air. J. Fluid Mech\ *.* 20:225-2
 
 Ozdogan, M., Rodell, M., Beaudoing, H.K., and Toll, D.L. 2010. Simulating the effects of irrigation over the United States in a land surface model based on satellite-derived agricultural data. Journal of Hydrometeorology 11:171-184.
 
+.. _Pageetal2002:
+
+Page, S.E., Siegert, F., Rieley, J.O., Boehm, H-D.V., Jaya, A., and Limin, S. 2002. The amount of carbon released from peat and forest fires in Indonesia in 1997. Nature 420:61-65.
+
 .. _Panofskyetal1977:
 
 Panofsky, H.A., Tennekes, H., Lenschow, D.H. and Wyngaard, J.C., 1977. The characteristics of turbulent velocity components in the surface layer under convective conditions. Boundary-Layer Meteorology, 11(3), pp.355-361. DOI:10.1007/BF02186086.

doc/source/tech_note/Urban/CLM50_Tech_Note_Urban.rst

@@ -21,7 +21,7 @@ The main changes in the urban model from CLM5.0 to CLM6.0 are (see below) 1) an
 
 The building energy model introduced in :ref:`Oleson and Feddema (2020) <OlesonFeddema2020>` accounts for the conduction of heat through interior surfaces (roof, sunlit and shaded walls, and floors), convection (sensible heat exchange) between interior surfaces and building air, longwave radiation exchange between interior surfaces, and ventilation (natural infiltration and exfiltration). Idealized HAC systems are assumed where the system capacity is infinite and the system supplies the amount of energy needed to keep the indoor air temperature (:math:`T_{iB}`) within maximum and minimum emperatures (:math:`T_{iB,\, \max },\, T_{iB,\, \min }` ), thus explicitly resolving space heating and AC fluxes. Anthropogenic sources of waste heat (:math:`Q_{H,\, waste}` ) from HAC that account for inefficiencies in the heating and AC equipment and from energy lost in the conversion of primary energy sources to end use energy are derived from :ref:`Sivak (2013) <Sivak2013>`. These sources of waste heat are incorporated as modifications to the canyon energy budget.
 
-An explicit AC adoption parameterization for the BEM was developed for CLM6.0 (:ref:`Li et al. (2024) <Lietal2024>`). An AC adoption parameter is introduced (:math:`p_{AC}` ). The AC flux is first calculated under saturated AC adoption (i.e., :math:`p_{AC}=100%` ). The actual AC flux removed from the indoor air is then scaled based on :math:`p_{AC}` and the waste heat added to the urban canyon due to AC energy use is also scaled by :math:`p_{AC}`. A global, spatially explicit dataset for the AC adoption rate was developed at country- and sub-country-level from sources such as the International Energy Agency (IEA), national surveys, scientific literature, and others.  For use with CLM, the AC adoption parameter was regridded to 0.9° latitude by 1.25° longitude and is read in for each of the three urban density classes using the file specified by the ``urbantv_streams`` namelist group (variables ``p_ac_MD``, ``p_ac_HD``, ``p_ac_TBD``). The maximum building interior temperature is also specified by the file in the ``urbantv_streams`` namelist group and is now considered to be the AC proxy setpoint in the parameterization and is set to 300K for all urban density classes (variables ``tbuildmax_MD``', ``tbuildmax_HD``, ``tbuildmax_TBD``). The explicit AC adoption parameterization in combination with the AC adoption rate dataset significantly improve CLM's performance in model building AC energy flux, both in magnitude and spatial variability (:ref:`Li et al. (2024) <Lietal2024>`).
+An explicit AC adoption parameterization for the BEM was developed for CLM6.0 (:ref:`Li et al. (2024) <Lietal2024a>`). An AC adoption parameter is introduced (:math:`p_{AC}` ). The AC flux is first calculated under saturated AC adoption (i.e., :math:`p_{AC}=100%` ). The actual AC flux removed from the indoor air is then scaled based on :math:`p_{AC}` and the waste heat added to the urban canyon due to AC energy use is also scaled by :math:`p_{AC}`. A global, spatially explicit dataset for the AC adoption rate was developed at country- and sub-country-level from sources such as the International Energy Agency (IEA), national surveys, scientific literature, and others.  For use with CLM, the AC adoption parameter was regridded to 0.9° latitude by 1.25° longitude and is read in for each of the three urban density classes using the file specified by the ``urbantv_streams`` namelist group (variables ``p_ac_MD``, ``p_ac_HD``, ``p_ac_TBD``). The maximum building interior temperature is also specified by the file in the ``urbantv_streams`` namelist group and is now considered to be the AC proxy setpoint in the parameterization and is set to 300K for all urban density classes (variables ``tbuildmax_MD``', ``tbuildmax_HD``, ``tbuildmax_TBD``). The explicit AC adoption parameterization in combination with the AC adoption rate dataset significantly improve CLM's performance in model building AC energy flux, both in magnitude and spatial variability (:ref:`Li et al. (2024) <Lietal2024a>`).
 
 Global urban properties were originally developed by :ref:`Jackson et al. (2010) <Jacksonetal2010>`. For each of 33 distinct regions across the globe and four urban density classes [tall building district (TBD), and high, medium, and low density (HD, MD, LD)], thermal (e.g., heat capacity and thermal conductivity), radiative (e.g., albedo and emissivity) and morphological (e.g., height to width ratio, roof fraction, average building height, and pervious fraction of the canyon floor) properties, are provided for each of the density classes. Building interior minimum and maximum temperatures are prescribed based on climate and socioeconomic considerations.  As described in :ref:`Oleson and Feddema (2020) <OlesonFeddema2020>` the urban properties dataset in :ref:`Jackson et al. (2010) <Jacksonetal2010>` was modified with respect to wall and roof thermal properties to correct for biases in heat transfer due to layer and building type averaging. Further changes to the dataset reflect the need for scenario development, thus allowing for the creation of hypothetical wall types, and the easier interchange of wall facets.  This slightly modified dataset was an option in CLM5.0.