Noah_LSM_USERGUIDE_2.7.1 LSM模式介绍及使用简介
THE COMMUNITY
Noah LAND-SURFACE MODEL (LSM)
User’s Guide
Public Release Version 2.7.1
Last Updated Feb. 9 2005
This document is filename NOAH_LSM_USERGUIDE_2.7.1 doc at
ftp://https://www.sodocs.net/doc/b512241389.html,/mmb/gcp/ldas/noahlsm/ver_2.7.1
Author: Kenneth Mitchell (NCEP/EMC)
Point of Contact: Vince.Wong@https://www.sodocs.net/doc/b512241389.html,, phone 301-316-5029 Collaborators: Mike Ek, Vince Wong, Dag Lohmann, Victor Koren, John Schaake, Qingyun Duan, George Gayno, Brian Moore, Pablo Grunmann, Dan Tarpley, Bruce Ramsay, Fei Chen, Jinwon Kim, Hua-Lu Pan, Ying Lin, Curtis Marshall, Larry Mahrt, Tilden Meyers, Paul Ruscher
TABLE OF CONTENTS
1.0 Introduction
2.0 Model Heritage
3.0 Directory Contents and Quick-Start Guide to Execution
4.0 Subroutine Summary and Calling Tree
5.0 Control File Contents and Function
6.0 Input Atmospheric Forcing File
7.0 LSM Initial Conditions
8.0 Specifying Model Parameters
9.0 Execution Output Files
10.0Technical References
1.0 INTRODUCTION
This User’s Guide provides execution guidance for and physical description of the public version of the community Noah LSM. This version of the Noah LSM is a stand-alone, uncoupled, 1-D column version used to execute single-site land-surface simulations. In this traditional 1-D uncoupled mode, near-surface atmospheric forcing data is required as input forcing (see Sec 6.0). This LSM simulates soil moisture (both liquid and frozen), soil temperature, skin temperature, snowpack depth, snowpack water equivalent (and hence snowpack density), canopy water content, and the energy flux and water flux terms of the surface energy balance and surface water balance. See Sec 10 for the lineage of key technical references.
The public server directory in which this User’s Guide resides also contains the complete, self-contained Noah LSM source code file, input control file, input atmospheric forcing file, and example execution-time LSM output files for a full one-year 1998 simulation. This simulation is valid at the Champaign, Illinois surface-flux site (40.01 N, 88.37 W) of NOAA/ARL investigator Tilden Meyers. See Sec 3 for a “Quick-Start” guide to executing the Noah LSM code in this directory to duplicate the cited 1998 simulation at this site. To execute Noah LSM simulations at other sites for other initial times, study Secs 5 through 8.
(Reminder: See Sec 3 for a “Quick-Start” guide to executing the Noah LSM.)
2.0 MODEL HERITAGE
Beginning in 1990, and accelerating after 1993 under sponsorship from the
GEWEX/GCIP/GAPP then GEWEX/GAPP Program Office of NOAA/OGP via collaboration with numerous GCIP/GAPP/GAPP Principal Investigators (PIs), the Environmental Modeling Center (EMC) of the National Centers for Environmental Prediction (NCEP) joined with the NWS Office of Hydrology (OH) and the NESDIS Office of Research and Applications (ORA) to pursue and refine a modern-era LSM suitable for use in NCEP operational weather and climate prediction models. Early in this effort, NCEP carried out an intercomparison of four LSMs, including 1) a simple bucket model, 2) the OSU LSM (known as the Coupled Atmospheric boundary layer - Plant – Soil, CAPS, model land-surface scheme in some PILPS studies), 3) the SSiB model, and 4) the Simple Water Balance model (SWB) of OH. The results of this intercomparison were reported in Chen et al. (1996, see references therein for the four cited LSMs). As a result of the good performance of the OSU LSM in this study and pre-existing hands-on experience with this LSM by various EMC staff members, including Hua-Lu Pan and Ken Mitchell, EMC chose the OSU LSM for further refinement and implementation in NCEP regional and global coupled weather and climate models (and their companion data assimilation systems). The results of the cited LSM intercomparison and the initial EMC refinements to the OSU LSM were reported in Chen et al. (1996).
At the beginning of the EMC LSM effort in 1990, the OSU LSM already had a 10-year history. Its initial development was carried out by OSU in a series of three papers (Mahrt and Ek, 1984; Mahrt and Pan, 1984; and Pan and Mahrt, 1987). As the EMC LSM effort unfolded during the 1990's, a series of NCEP extensions to the OSU LSM were a) added by EMC and its
GCIP/GAPP and other collaborators and b) tested and validated in both uncoupled and coupled studies (see review of these in Mitchell et al, 1999, 2000, and Ek et al. 2003). At NCEP, the LSM was first coupled to the operational NCEP mesoscale Eta model on 31 Jan 96, with significant Eta LSM refinements subsequently implemented on 18 Feb 97, 09 Feb 98, 03 Jun 98, 24 Jul 01, 26 Feb 02 12 June 02. In 1999, with a) the new addition and testing of frozen soil and patchy snow cover physics in the uncoupled LSM used for the NCEP-OH submission to PILPS-2d (Valdai, Russia), and b) the growing number of external user requests for access to and use of the NCEP LSM (e.g. GCIP/GAPP PIs), we decided the NCEP LSM had advanced to a stage appropriate for formal public release (first in March 99).
In 2000, given a) the advent of the "New Millenium", b) a strong desire by EMC to better recognize its LSM collaborators, and c) a new NCEP goal to more strongly pursue and offer "Community Models", EMC decided to coin the new name "NOAH" for the LSM that had emerged at NCEP during the 1990s:
N: National Centers for Environmental Prediction (NCEP)
O: Oregon State University (Dept of Atmospheric Sciences)
A: Air Force (both AFWA and AFRL - formerly AFGL, PL)
H: Hydrologic Research Lab - NWS (now Office of Hydrologic Dev -- OHD)
We in EMC strive to explicitly acknowledge both the multi-group heritage and informal "community" useage of this LSM, going back to the early 1980’s. Since its beginning then at Oregon State University, the evolution of the present Noah LSM herein has spanned significant ongoing development efforts by the following groups:
NCEP/EMC: NCEP Environmental Modeling Center (EMC)
(Mitchell, Ek, Lohmann, Grunmann, Lin, Marshall, Chen, Rogers, Manikin,
Pan)
OSU: Oregon State University
(Mahrt, Pan, Ek, Kim, Ruscher)
HRL: NWS Hydrology Lab - formerly Office of Hydrology
(Schaake, Koren, Duan)
AFWA: Air Force Weather Agency - formerly AFGWC
(Gayno, Mitchell, Moore)
AFRL: Air Force Research Lab - formerly AFGL and PL
(Mitchell, Chang, Hahn, Yang)
In addition to “in-house” Noah LSM development and validation by the above organizations, the following external PIs (primarily GCIP/GAPP), have also performed valuable validations of the Noah LSM and its immediate NCEP 1990's predecessors:
E.H. Berbery and Rasmusson U. Maryland (ARM/CART)
C. Marshall, Basara, and Crawford U. Oklahoma (OU Mesonet)
Bastidas, Burke, Yucel, Shuttleworth,
Sooroshian U. Arizona (ARM/CART, AZNET)
A. Robock and L. Luo Rutgers U. (OU Mesonet, ARM/CART) A.K. Betts Atmospheric Res Inc (ISLSCP/FIFE)
C.D. Peters-Lidard, Wood Princeton U. (TOPLATS extensions)
L. Hinkelman and Ackerman Penn State U. (ARM/CART)
T.H. Chen, W. Qu, Henderson-Sellers, et al. R MIT (PILPS-2a)
E. Wood, Lettenmaier, Liang, Lohmann: Princeton U. (PILPS-2c)
A. Schlosser, A.G. Slater, Robock, et al. U. Maryland (PILPS-2d)
R. Angevine NOAA/AL (Flatland Exp)
L. Bowling and D. Lettenmaier Univ. Washington (PILPS-2e)
A. Boone and J. Noilhan Meteo-France (Rhone/GLASS)
K. Arsenault, B. Cosgrove, P. Houser NASA-HSB (LDAS)
See Sec 10 for technical references on the above external validations.
Lastly, o ne crucial collaborator deserves special mention, namely the NESDIS Office of Research and Applications (Tarpley, Ramsay, Gutman, Kogan, Bailey), which has been the source of critical global surface fields of a) vegetation greenness and its seasonality and b) realtime snow cover, plus important GOES, satellite-based, hourly surface validation fields of c) land surface skin temperature and d) solar insolation, both on a 0.50-degree lat/lon CONUS grid.
3.0 DIRECTORY CONTENTS AND QUICK-START GUIDE TO EXECUTION
3.1Basic_with_validation
The directory /mmb/gcp/ldas/noahlsm/ver_2.7.1/basic_with_validation on anonymous server https://www.sodocs.net/doc/b512241389.html, contains sixteen files as follows: 1) this User’s Guide (file NOAH_LSM_USERGUIDE_2.7.1.doc), 2-3) the source code file split for the User's
convenience into two mutually exclusive files representing a) "driver" routines and b)
"physics" routines, 4) an input control file that defines model configuration and provides initial conditions, 5) an input atmospheric forcing file, 6) a doc file describing the source and valid period/location of this forcing file, 7-9) an input "namelist" file triad that allows input of non-default physical parameters, 10-14) five execution-time output files,
resulting from an entire one-year 1998 simulation valid near the Champaign, Illinois
surface-flux site of Tilden Meyers of NOAA/ARL. This site is located at the lat/lon
coordinates of (40.01 N, 88.37 W), 15) this user’s guide in text format, 16) a tar file that contains the aforementioned 15 files. The16 filenames are listed below:
Filename Contents
1 -- NOAH_LSM_USERGUIDE_2.7.1.doc This User's Guide
2 -- DRIVER_WITH_VALIDATION.f "DRIVER" family of routines of Noah_LSM
3 -- NOAH_LSM_SRC_2.7.1.f "PHYSICS" family of routines of Noah_LSM source code
4 -- controlfile_ver_2.7.1 Input control file
5 -- forcing98_with_validation.dat Input near-surface atmospheric forcing file
6 -- CHAMP_IL.doc Observing site description
7 -- namelist_filename.txt 1-line 50-char name of namelist-read input file
8 -- soil_veg_namelist_ver_2.7.1 namelist-read input file
9- doitall_2.7.1.sh Execute DRIVER and SRC
10- PRTSCREEN.TXT.Z Execution “print * “ screen output
11- DAILY.TXT.Z Execution Output File 1
12- HYDRO.TXT.Z Execution Output File 2
13- THERMO.TXT.Z Execution Output File 3
14- OBS_DATA.TXT.Z Execution Output Data File
15- README This user’s guide in text format
16- NOAH_LSM_2.7.1.tar tar file that contains the above 15 files
All files are text files, except files NOAH_LSM_USERGUIDE_2.7.1.doc and CHAMP_IL.doc, which are MS Word files. Download the tar file basic_with_validation.tar that contains all 15
files to your workstation. Use Unix command “tar –xvf basic_with_validation.tar” to create a Proceed with a Noah LSM execution test as described below.
First uncompress the “*.Z” files with the Unix uncompress command.
The uncompress yields five upper-case “*.TXT” files. These TXT files are output files. Move these “TXT* files to a separate sister directory for later comparison to the equivalent output files from your own local execution.
The four lower-case files given by filenames
controlfile_ver_2.7.1
forcing98_with_validation.dat
namelist_filename.txt
soil_veg_namelist_ver_2.7.1
are the four input files required during the execution of lsm.x. The “controlfile” (see Sec 5) contains model configuration variables such as number and thickness of soil layers, number and length of time steps, initial date/time of the simulation, lat/lon location of the simulation site, initial conditions for all state variables, and site-specific land classifications (integer indexes for vegetation-type, soil-type, and surface-slope category).
The file obs98.dat (see Sec 6) contains one year’s worth (1998) of 30-min observed atmospheric forcing data and independent observed verification data (e.g. surface energy fluxes and soil temperature) valid at the Champaing, Illinois surface-flux site operated and maintained by Tilden Meyers of NOAA/ARL. The site is located at the lat/lon coordinates of (40.01 N, 88.37 W). Now invoking
“doitall_2.7.1.sh”
will launch and complete the 1998 one-year LSM simulation for the aforementioned Illinois site, producing the same 5 “*.TXT” output files that you obtained originally from the NCEP server. Normal termination of the execution is marked by the termination message “STOP: 0”. Since all the “*.TXT” files are ascii files, one can and should confirm that the 5 output files from the local simulation agree very closely with the originally downloaded output files from NCEP.
The output file PRTSCREEN.TXT contains the output from “Print *” write statements in the MAIN program. In this Version 2.7.1, these are the block of three “Print *” statements located within the time-step loop in the PROGRAM MAIN source shortly after the return from CALL SFLX . These three Print * statements output the time step counter and the small surface energy balance residual during each of the first 50 time steps and then every 50 time steps thereafter. The other four output files are the execution output data files of greater interest and their contents are described in Sec 9.
One important degree of freedom regarding these remaining four output files must be cited here. The unit numbers for these output files are 43, 45, 47, and 49, which are explicitly assigned in PROGRAM MAIN (via variable names NOUT1, NOUT3, NOUT5, and NDAILY). The sign of these assigned unit numbers controls whether the output is ascii or binary. The sign of all four
unit numbers is determined by a signed parameter (IBINOUT) read-in from the control file (see Sec 5). When the sign of IBINOUT is positive (negative), the format of these four output files is binary (ascii). When the output format is ascii (binary) then the extension *.TXT (*.GRS, meaning GrADS-readable) appears on the generated filename. The ascii choice (negative unit number sign) was invoked in the default control run you obtain from the server.
3.2Basic
The directory /mmb/gcp/ldas/noahlsm/ver_2.7.1/basic on anonymous server
https://www.sodocs.net/doc/b512241389.html, contains the same files as in the directory basic_with_validation except for 2 different files DRIVER_BASIC.f and forcing_basic98.dat. The file CHAMP_IL.doc is missing as it is irrelevant. The basic driver DRIVER_BASIC.f reads the near-surface input file forcing_basic98.dat that contains only the 7 observed variables required for constructing Noah LSM forcing (cf. Sec. 6.2). This basic driver is designed for reading data from regular surface sites that do not measure surface fluxes or subsoil properties.
4.0 SUBROUTINE SUMMARY AND CALLING TREE
Below, we describe PROGRAM MAIN in the "Driver family" of subroutines (file
DRIVER_WITH_VALIDATION.f or DRIVER_BASIC.f as described in Sec. 3.2) and the "Physics family" of subroutines (file NOAH_LSM_2.7.1.f ), comprised of physics "sub-driver" routine SFLX and all subordinate subroutines.
4.1 The Driver Routines
Briefly the ten main steps of the MAIN program are:
1)read in control file ( model configuration, site characteristics, and initial conditions)
2)open output file unit numbers
3)invoke time-step loop (including optional spin-up loop if indicated by control file)
4)read atmospheric forcing data and change its sign and units as expected by SFLX
5)interpolate monthly-mean surface greenness and albedo to julian day of time step
6)assign downward solar and longwave radiation from input forcing
7)calculate actual and saturated specific humidity from input atmospheric forcing
8)assign wind speed from input forcing
9)invoke LSM physics (CALL SFLX) to update state variables / sfc fluxes over one time step
10) write simulation output data each time step to four output files
The section in driver PROGRAM MAIN associated with each of the above ten steps is clearly delineated with comment line "DRIVER STEP n".
NOTE: The section of PROGRAM MAIN for Step 6 includes optional code (presently commented out) for calculating the downward radiation from the input air temperature and humidity if the input forcing file does not provide it.
NOTE: The section of PROGRAM MAIN for Step 8 includes optional code (presently commented out) for invoking a User-provided routine to calculate the surface exchange coefficient for heat (Ch) in place of the default scheme.
PROGRAM MAIN Calling Tree
-READCNTL: read control file (including LSM initial conditions and site characteristics) ------------ Begin optional Multi-year Spin-Up Loop: if invoked by control file ------------- ---------------------------------------- Begin: Time Step Loop -------------------------------------
-READBND : read atmospheric forcing data (and observed validation variables)
-MONTH-D: interpolate monthly albedo and veg greenness to current julian day -- JULDATE: determine julian day for current time
-QDATAP: calculate actual and saturated specific humidity
-- E (function) calculate vapor pressure
-DQSDT (function): slope of sat specific humidity wrt air temp (needed in PENMAN) -- DQS (function) intermediate value for routine dqsdt
-SFLX: call to family of physics routines (see Sec 4.2) **** key call ****
-PRTDAILY: write daily total values to output file 1 (once a day only) -PRTHYDF: write LSM water related variables to output file 2 (every time step) -PRTHMF: write LSM energy related variables to output file 3 (every time step) -PRTBND: write out input atmospheric forcing to output file 4 (every time step) -------------------------------- End: Time Step Loop ---------------------------------------------- -------------------------End: Optional Multi-year Spin-Up Loop---------------------------------
-STOP 0
4.2 The SFLX Family of Subroutines
The SFLX family of subroutines contain the physics of the LSM and is rather self-contained. Each user should become familiar with the argument list of SFLX. This argument list is thoroughly documented at the top of subroutine SFLX. Once becoming familiar with the argument list, users could if they so choose create their own MAIN driver program with reasonably little effort. Calling SFLX each time step updates and returns all the LSM state variables and all the surface energy balance and surface water balance terms. In using SFLX in a coupled atmospheric model, the output arguments needed from SFLX are:
ETA - latent heat flux
H - sensible heat flux
T1 - skin temperature (from which to calculate upward longwave radiation) ALBEDO - (including snowpack effects) for calculating upward solar radiation SUBROUTINE SFLX Calling Tree
REDPRM -- set land-surface parameters
-- set soil-type dependent parameters
-- set veg-type dependent parameters
-- set other land-surface parameters
SNO_NEW – update snow depth and snow density to account for new snowfall
SNFRAC – determine snow cover fraction
ALCALC – determine surface albedo (including snow cover fraction)
TDFCND – compute soil thermal diffusivity
SNOWZ0 – compute snow roughness length (currently a null/no effect process)
SFCDIF -- calculate surface exchange coefficient for heat/moisture
PENMAN – compute potential evaporation
CANRES – compute canopy resistance
NOPAC – this path invoked if ZERO snowpack on ground and zero snowfall (frozen precip)
-- surface skin temperature updated via surface energy balance
SMFLX – compute a) surface water fluxes and b) layer soil moisture update
DEVAP- compute direct evaporation from top soil layer
TRANSP – compute transpiration from vegetation canopy
SRT – compute time-rate-of-change of soil moisture
WDFCND – compute hydraulic conductivity and diffusivity
SSTEP – forward time-step integration of soil moisture rate-of-change
ROSR12 – tri-diagonal matrix solver
TDFCND – compute soil thermal diffusivity
SHFLX – compute a) ground heat flux and b) layer soil temperature update
HRT – compute time-rate-of-change of soil temperature
TDFCND – compute soil thermal diffusivity (dependent on soil moist.)
TBND – determine soil layer interface temperature
SNKSRC –(function) compute heat sink/source from soil ice phase change
TDFCND – compute soil thermal diffusivity
FRH2O – (function) calculate subzero unfrozen soil water (or HRTICE – as in HRT, but for sea-ice pack)
HSTEP – forward time step integration of soil temperature rate-of-change
ROSR12 – tri-diagonal matrix solver
SNOPAC – this path invoked if NONZERO snowpack on ground and/or NONZERO snowfall -surface skin temperature updated via surface energy balance
-new patchy snow cover treatment in above
-snowmelt computed if thermal and available energy conditions warrant
SMFLX – see above
DEVAP – see above
TRANSP – see above
SRT – see above
WDFCND – see above
SSTEP – see above
ROSR12 – see above
SHFLX – see above
HRT – see above
TDFCND – see above
TBND – see above
SNKSRC – see above
TDFCND – see above
FRH2O – see above
HSTEP – see above
ROSR12 – see above
SNOWPACK – update snow depth and snow density owing to snow compaction NOTES on SFLX Calling Tree:
1 – Both the NOPAC and SNOPAC branches treat freezing processes within soil
2 – Calling sequences under NOPAC and SNOPAC via SMFLX and SHFLX are very similar
3 – Snowpack physics in SNOPAC are treated mainly “in-line”, before calls to SMFLX/SHFLX
4 – SHFLX and subordinates do heat fluxes and soil temperature update
5 – SMFLX and subordinates do water fluxes and soil moisture update
-- SMFLX operates independently of the soil thermodynamics (SHFLX) and can stand
alone, requiring only inputs of precipitation and potential evaporation
-- SHFLX cannot operate independently of soil hydraulics, unless thermal conductivity
dependence on soil moisture dependence is removed (in routine TDFCND)
5.0 CONTROL FILE CONTENTS AND FUNCTION
The filename of the control file is “controlfile_ver_2.7.1”. The user may want to have a printout of the control file handy (about one page) when reviewing the comments below.
The control file is read-in early in the MAIN program and provides inputs of the following types of information: a) valid location and start date/time of simulation, b) model configuration,
c) name of input forcing file, d) integer indexes for land-sfc classes for the site, e ) initial values of all the model state variables.
NOTE: The control file does not provide model physical parameters, except for the lower boundary condition on the soil temperature (which should be assigned the value of the annual mean sfc air temperature for the simulation location). Physical parameters are set in subroutine REDPRM and many of these parameters are dependent in REDPRM on the veg-type index and soil-type index read from the control file.
The control file consists of 30 data lines that contain the following:
Line 01: LAT - simulation site latitude (positive N from equator, hundredths of a degree)
Line 02: LON - simulation site longitude (positive W from Greenwich, hundredths of a degree) Note: The above serve only to document the valid site of the input forcing data.
The physics do not use the above, since forcing data provides downward solar radiation. Above would be needed by a MAIN driver that had to calculate downward solar radiation Line 03: IBINOUT - either positive interge "1", or negative integer "-1".
Negative sign invokes ascii text output files with extension *.TXT
Postive sign invokes binary output files with extension *.GRS -denoting GrADS readable
Line 04: JDAY - Integer Julian Day (1-366) of start of forcing data (start of simulation)
Line 05: TIME - 4-digit "hhmm" integer time of day (local) at start of forcing data, hh is 2-digit hour (0-23) and mm is 2-digit minute (0-59).
Note: Except for use of JDAY to to temporal interpolation of monthly greenness and albedo read-in later below, the above JDAY and TIME serve only to document the valid start date/time of the input forcing data. The physics do not use the above, since forcing data provides downward solar radiation. Above would be needed by a MAIN driver that had to calculate downward solar radiation
Line 06: NCYCLES – number of times the integration will cycle through the input forcing data (useful for multi-year spin-up runs, wherein input forcing file spans one complete year) Line 07: SYDAYS - number of days in spin-up year (either 365 or 366)
(relevant only if NCYCLE is 2 or greater)
Line 08: L2nd_data: logical variable: value of .true. or .false.
if TRUE: then NCYCLES must be set to 2 or greater, and thus invokes spin-up runs of
NCYCLE-1 spin-up years with first forcing file given below, followed by 1 final cycle
(not necessarily full year)executed from second forcing file below and representing the
final production run period. Will write output only during final cycle, unless two forcing files have the same name, then will write output from each cycle
if FALSE: then only first named forcing file is used, still for the number of cycles given by NCYCLE, and will write output from every cycle
Note: The true option for L2nd_data is useful for multi-year "PILPS-type" spin-up runs For forcing files spanning only a partial year, L2nd_data should be false and NCYCLE=1 Line 09: NRUN is the total number of simulation time steps per cycle.
Line 10: DT – floating point length of time step (secs) used in physical integration
Note: DT should NOT be larger than one hour (3600 secs)
Note: There must be one forcing data record in forcing file for each time step
Line 11: NSOIL - integer number of soil layers
Note: NSOIL must be 2 or greater, NOT to exceed 20, strongly recommend at least 4
Line 12: Z – height in meters above ground of atmospheric forcing data
Note: In observed forcing data, the height of the temperature/humidity observation (e.g. 2 m) is often different from the height of the wind observation (e.g. 10 m ). When that is the case, we recommend using the height of the wind observation for Z.
Line 13: SLDPTH - thickness values for the NSOIL soil layers in meters (chosen by user), starting with the uppermost layer and proceeding downward
Note: We recommend that each succeeding soil layer downward not exceed 3 times the thickness of the soil layer above it. For the common 4-layer configuration, we recommend
Layer 1: 10 cm (.10 m)
Layer 2: 30 cm (.30 m)
Layer 3: 60 cm (.60 m)
Layer 4:100 cm (1.0 m)
Note: The physical equations in the LSM predict the soil moisture/temperature state variables at the midpoint of each model soil layer.
NOTE:!! Sum total of all soil layer thicknesses should not exceed about 2/3 of depth parameter ZBOT. The lower boundary condition TBOT of soil temperature is applied at the depth specified by parameter ZBOT, whose current default value of -8.0 meters is set in routine REDPRM (ZBOT follows negative sign convention for soil depth), but this default can be changed via the optional NAMELIST I/O in REDPRM.
Line 14: - filename of the first input forcing file (up to 72 characters)
Line 15: - filename of the second input forcing file (up to 72 characters)
Note: see above discussion of logical variable "L2nd_data
Note: the two forcing files may be the same name (used for both spin-up and production years) NOTE !! : User should contact NCEP Point of Contact given at top of Page 1 for recommended values for Lines 12-18
Line 16: SOILTP - soil type integer index (range 1-9), see definitions in routine REDPRM
Line 17: VEGTYP veg type integer index (range 1-13), see definitions in routine REDPRM Line 18: SLOPTYP sfc slope integer index (range 1-9), see definitions in routine REDPRM Note: SLOPTYP is a sfc slope category (flat, steep, mixed, etc) used in the bottom drainage Line 19: ALBEDO – 12 monthly values of surface albedo fraction (snow-free) for simulation site Note: LSM physics will internally add snow cover effects to ALBEDO
Line 20: SHDFAC - 12 monthly values of green vegetation fraction for simulation site
NOTE !! See contact point at top of this User's Guide to get monthly vegetation greenness values for your simulation site of interest.
NCEP now sets monthly SHDFAC using the global database and publication of
Gutman, G. and A. Ignatov, 1998: The derivation of the green vegetation fraction from
NOAA/AVHRR for use in numerical weather prediction models. International Journal of Remote Sensing, 19, 1533-1543.
This latter work provides a 5-year, monthly mean, global database of green vegetation fraction at 0.144 degree resolution, obtained from NDVI. The authors forcefully argue that the two AVHRR channels that are used to derive NDVI do NOT provide sufficient degrees of freedom to
derive BOTH vegetation greenness and LAI independently. They instead argue for embracing all the seasonality of vegetation in the greenness fraction and holding the LAI at a fixed constant annual value in the range of 1-5 (thus LAI becomes a tuning parameter). NCEP has obtained reasonable behavior with LAI=4.
Line 21: SNOALB – maximum albedo expected over deep snow
Note: NCEP takes the above from the 1-degree, N. Hemisphere, digital database of Robinson, D.A., and G. Kukla, 1985: Maximum surface albedo of seasonally snow-
Covered Lands in the Northern Hemisphere. J. Climate Appl. Meteor., 23, 1626-1634
(See Fig. 4 therein for depiction from digital database).
Line 22: ICE – Flag to invoke sea-ice physics (always set to 0 for land-mass simulations) Note: The integer flag “ICE” forces branch to sea-ice physics in LSM.
Be aware that this ICE flag has no bearing on soil ice physics in NCEP LSM.
Line 23: TBOT – set to the climo annual mean sfc air temperature (K) for the modeled site
.
Note: TBOT serves as the annually fixed, soil-temperature bottom-boundary condition at a soil depth of ZBOT. ZBOT is currently set at a default 8-meter depth (-8.0) in routine REDPRM. ZBOT is the assumed nominal soil depth where the amplitude of the soil-temperature annual cycle is near zero (e.g. about double the e-folding depth in the soil of the annual cycle of surface air temperature).
Initial conditions for all state variables follows:
Line 24: T1 – initial skin temperature (K). Can be set to initial air temperature. Model physics rapidly spins this up in first few 2-3 time steps.
Line 25: STC (1-NSOIL): initial soil temperature (K), in each soil layer
Line 26: SMC (1-NSOIL): initial volumetric total soil moisture (liquid and frozen) in each layer (usually in the range .1-.43)
Note: Initial SMC should not exceed soil saturation (porosity), as set in routine REDPRM for given soil class.
Line 27: SH2O (1-NSOIL): initial volumetric liquid soil moisture (unfrozen) in each layer Note: initial SH2O must not exceed porosity, nor exceed initial SMC
NOTE: During conditions of no soil freezing, SH2O=SMC in each layer.
NOTE: Initializing soil ice (case of SH2O less than SMC) is very difficult. Recommend starting the model run in the warm season and letting the physics spin-up soil ice, or running multi-year spin-up cycles.
Line 28: CMC – initial canopy water content (m). Set to zero as physics rapidly spins this up. Line 29: SNOWH – initial snow depth (m)
Line 30: SNEQV – initial water equivalent (m) of above snowdepth. If not observed, dividing SNOWH by 5 gives a nominal initial value.
6.0ATMOSPHERIC FORCING FILE
6.1 Forcing with Validation
As is typical with many off-line, uncoupled LSMs, the NCEP LSM requires the following near-surface atmospheric forcing data, preferably at 30-minute time intervals (or interpolated to
30-minute time intervals or smaller from say 1-6 hour interval observations -- Aside note: for observation intervals longer than 1-hour, the incoming surface solar insolation needs to be interpolated with a solar zenith angle weighting, in order to capture the full amplitude of the diurnal solar insolation).
Air temperature at height Z above ground
Air humidity at height Z above ground
Surface pressure at height Z above ground
Wind speed at height Z above ground
Surface downward longwave radiation
Surface downward solar radiation
Precipitation
For the example one-year LSM simulation provided with this User’s Guide, we were extremely fortunate to benefit from the collaboration of GCIP/GAPP-sponsored PI Tilden Meyers of NOAA/ARL, who operates a flux site located just south of Champaign, IL (40.01 N lat, 88.37 W lon).
The site characteristics and observing instrumentation are described in the MS Word document CHAMP_IL, provided by courtesy of Tilden Meyers, and available in same directory as this User’s Guide.
The 1998 forcing file from the above flux site is available as filename
“forcing98_with_validation.dat” in the same directory as this User’s Guide. This file contains one record for each 30-minute observation time and the file spans the entire calendar year of 1998 (hence 2 X 24 X 365 = 17520 records). Each 30-min record provides the following 33 observed variables (including the 7 required LSM forcing variables, marked by “**”), listed in the order they appear in each record of the file:
jday Julian Day
time LST, half hour ending
w_speed propeller anemometer (10 meters, Bondville ISIS)
w_dir wind direction (10 meters, Bondville ISIS)
** Ta air temperature (C), at 3 m
** RH relative humidity at 3 m (list continued)
** Pres surface pressure in mb
** Rg incoming solar radiation (W/m2)
Par_in incoming visible radiation (0.4-0.7 um) in uE/m2/s
Par_out outgoing or reflected visible light
Rnet net radiation (W/m2)
GHF soil or ground heat flux (W/m2)
** rain total rain for half hour (inches)
wet wetness sensor (in voltage with higher values indicating wetness)
IRT surface or skin temp (C)
2_cm soil temp at 2 cm (C)
4_cm soil temp at 4 cm
8_cm soil temp at 8 cm
16_cm soil temp at 16 cm
32_cm soil temp at 32 cm
64_cm soil temp at 64 cm
** u_bar average wind vector speed at 6-meters (m/s)
u’w’ kinematic shear stress (m2/s2)
u’2 streamwise velocity variance (m2/s2)
v’2 crosswind velocity variance (m2/s2)
w’2 vertical velocity variance(m2/s2)
H sensible heat flux (W/m2)
LE latent energy flux (W/m2)
CO2 CO2 flux (mg CO2/m2/s)
** LW_in downwelling longwave from sky (W/m2)
sm_5 soil volumetric water content at 5 cm zone (after November 19 1997) sm_20 soil volumetric water content at 20 cm zone (after November 19 1997) sm_60 soil volumetric water content at 60 cm zone (after November 19 1997) In the LSM, program MAIN reads in all 33 of the above variables at each time step via the call to subroutine READBND, which also fills in occasional missing observations. Missing obs are very sparse and virtually always involve missing values of the wind speed (u_bar at 6 m), for which the READBND software substitutes (w_speed at 10 m with a reduction factor). Finally, the last section of routine READBND performs unit conversions on “rain”, “Ta”, and “Pres” to convert them to the units expected in the call to SFLX .
In addition to the LSM-required atmospheric forcing variables in the above list, the other variables in the list represent either a) independent validation data or b) useful initial conditions for the LSM state variables. LSM initial conditions are discussed in the next section.
At each time step in the MAIN program, after the return from the physics update in CALL SFLX, useful LSM validation data from the above observation file is written out to validation
output file OBS_DATA.TXT via call to routine PRTBND (e.g. LE, H, GHF, RNET, IRT, and the layer by layer soil moisture and temperature).
6.2Basic Forcing
The basic input near-surface atmospheric forcing file forcing98_basic.dat is a subset of the input file forcing98_with_validation.dat described in Section 6.1. This basic input forcing file is located at: ftp://https://www.sodocs.net/doc/b512241389.html,/mmb/gcp/ldas/noahlsm/ver_2.7.1/basic
This file contains one record for each 30-minute observation time and the file spans the entire calendar year of 1998 (hence 2 X 24 X 365 = 17520 records). Each 30-min record provides the following 9 observed variables (including the 7 required LSM forcing variables, marked by
“**”), listed in the order they appear in each record of the file:
jday Julian Day
time LST, half hour ending
** Ta air temperature (C), at 3 m
** RH relative humidity at 3 m
** Pres surface pressure in mb
** Rg incoming solar radiation (W/m2)
** rain total rain for half hour (inches)
** u_bar average wind vector speed at 6-meters (m/s)
** LW_in downwelling longwave from sky (W/m2)
7.0 LSM INITIAL CONDITIONS
The LSM requires input values (read-in from control file in routine READCNTL, see Sec 5 for details on units) of the following state variable initial conditions :
1 – SMC: total volumetric soil moisture (liquid and frozen) in each soil layer
2 – SH2O: liquid volumetric soil moisture in each soil layer
3 – STC: temperature in each soil layer
4 – T1: skin temperature
5 – CMC: canopy water content
6– SNOWH: snow depth
7 - SNEQV: water-equivalent snow depth
Typically, a number of these state variables are not observed at a given validating observation site. The following initial variables were not available in the site observation file (obs98.dat): SNEQV, SNOWH, CMC, nor SMC (and SH2O) below 60 cm
Since January 1998 was mild (El’Nino) at the given site, we assumed a) zero snow cover (SNOWH=0.0, SNEQV=0.0) and b) zero soil ice (SMC=SH2O), plus we set CMC=0.
While we in general found the physical behavior of the observed data in file obs98.dat to be very good, inspection of the observed soil moisture at the 20 and 60 cm levels showed them to be virtually time invariant over the entire year, despite substantial wetting and drying periods. Hence their accuracy is very suspect.
It is typical for LSM simulations at a particular observation site to be hampered by non-observed (e.g. snowdepth, frozen soil moisture, deep soil moisture ) or ill-observed initial state variables (.e.g. soil moisture). Facing this dilemma, the Project for Intercomparison of Land-Surface Process Schemes (PILPS) has come to urge modelers to use a one-year spin-up protocol, whereby the simulation for a desired period (1998 here) is preceded by a spin-up year (say 1997 in this case) where the spin-up year forcing is repeated several years to allow the LSM to essentially achieve equilibrium.
Tilden Meyers provided us with the 1997 forcing data for his site, and we proceeded to execute the PILPS-recommended spin-up protocol to provide all initial soil states for the one-year 1998 production run provided in this directory.
Specifically, in a prior run using the same model configuration as in the control file given here and using L2nd_data = .false., NCYCLES= 10, and the aforementioned 1997 forcing file we call "obs97.dat", we executed a 10-year spin-up run over the 1997 annual cycle in order to derive initial conditions of soil state and snow state (turned out zero snowpack, because of warm fall and early winter in 1997) for the 1998 production run provided here in the directory with this User's Guide. In practice, a full 10-years of spin-up is not needed. We generally recommend 3-5 years of spin-up.
8.0 SPECIFYING MODEL PARAMETERS
The vast majority of the Noah LSM land-surface parameters are set in subroutine REDPRM. However, the assignment of some land-surface parameters have not yet been “collected” into the REDPRM setting and remain buried deep in the LSM code. We feel these exceptions are primarily parameters of secondary or tertiary importance. A few exceptions may be some parameters used in the snowpack physics, such as the parameter that controls the amount of supercooled water allowed in the soil over a range of sub-freezing temperatures. We are working to identify such parameters and bring them into the REDPRM setting in a future release. In a broader sense, one should also consider the number (NSOIL) and thickness (SLDPTH) of the soil layers (especially thickness of top soil layer) specified in the control file to be adjustable parameters.
Before proceeding further in this section, the reader should have on hand a copy of the subroutine REDPRM.
In REDPRM, we define the NAMELIST named "/SOIL_VEG/", which includes ALL the parameters defined in REDPRM, including parameter arrays whose elements depend on soil type, vegetation type, or slope type. Moreover, this namelist includes three variables that respectively define the number of classes (up to a maximum of 30) that we carry for soil type,
vegetation type, and slope type. With the powerful and robust flexibility of the namelist construct, we can even make wholesale changes to the soil and vegetation classification scheme used and the soil and vegetation parameters associated with the change in classification. Thus via the namelist read, we can change as little as one single universal parameter, or multiple- element parameter arrays associated with a classification, or the number of classification categories themselves, or a combination of these, all without any recompiling of source code. One exercises the above flexibility through the input filename called "namelist_filename.txt", which is read-in by routine REDPRM. This 1-line 50-char text file provides the name of the namelist file, which the routine REDPRM then reads in as well. By this mechanism, one can carry multiple namelist files (providing different parameter sets) in the same execution directory. The contents of the 1-line file "namelist_filename.txt" thus acts as a pointer to the namelist file you wish to read-in during a given execution.
Every namelist file so pointed to must begin with the following syntax:
$SOIL_VEG LPARAM = .FALSE.$
or
$SOIL_VEG LPARAM = .TRUE.$
with the latter followed by at least one or more defined parameter values.
We recall that the beginning of Sec 3 listed all the filenames in the directory /ver_2.7.1 with this User's Guide (Noah_LSM_USERGUIDE_2.7.1.doc). Inspecting the contents of filename "namelist_filename.txt" therein, we find that this file points to the filename
""soil_veg_namelist_ver_2.7.1". On inspection we find the contents of this file to be
$SOIL_VEG LPARAM = .FALSE.$ ,
hence ALL the default values of the parameters defined in REDPRM will be retained unchanged. If the contents of "namelist_filename.txt" instead pointed to filename "namelist_chg_example", then we find on inspection that the contents of the latter file are
$SOIL_VEG LPARAM = .TRUE.$
$SOIL_VEG NROOT_DATA =
3,3,3,3,3,3,2,2,2,2,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 $
$SOIL_VEG Z0_DATA(7) = 0.15 $
$SOIL_VEG REFKDT_DATA = 1.0 $
In the above example, our execution will utilize 1) new values for all the elements of array NROOT, 2) a new value for the 7-th element of the array of roughness lengths (this element corresponding to veg class #7, or perennial grassland), and 3) a new value for the scalar surface runoff parameter REFKDT.
Below, we will review ALL the parameters defined in REDPRM. All these parameters are included in the NAMELIST /SOIL_VEG/, which is specified in routine REDPRM as NAMELIST /SOIL_VEG/ SLOPE_DATA, RSMTBL, RGLTBL, HSTBL, SNUPX,
& BB, DRYSMC, F11, MAXSMC, REFSMC, SATPSI, SATDK, SATDW,
& WLTSMC, QTZ, LPARAM, ZBOT_DATA, SALP_DATA, CFACTR_DATA,
& CMCMAX_DATA, SBETA_DATA, RSMAX_DATA, TOPT_DATA,
& REFDK_DATA, FRZK_DATA, BARE, DEFINED_VEG, DEFINED_SOIL,
& DEFINED_SLOPE, FXEXP_DATA, NROOT_DATA, REFKDT_DATA, Z0_DATA,
& CZIL_DATA, LAI_DATA, CSOIL_DATA, SMLOW_DATA, SMHIGH_DATA
In the above list, there are five kinds of land-surface parameters, reviewed in order below.
a)single universal values
b)values dependent on the soil class index (default categories are 1- 9)
c) values dependent on the vegetation class index (default categories are 1-13)
d) values dependent on the surface slope index (default categories are 1-7)
e) parameters specifying the numbers of vegetation, soil, and slope classes
A) Universal values (16) (current default value in this release listed)
CZIL = 0.20: Zilintikevich parameter (range 0.0 - 1.0), recommended range 0.2 - 0.4
Note: CZIL is a tuneable parameter, which controls the ratio of the roughness length for heat to the roughness length for momentum, and is known as the Zilintikevich coefficient. This parameter effectively allows tuning of the aerodynamic resistance of the atmospheric surface layer. Increasing CZIL increases aerodynamic resistance. For a full description and example impacts of this primary parameter, see the article by
Chen, F, Z. Janjic, and K. Mitchell, 1997: Impact of the atmospheric surface-layer
parameterizations in the new land-surface scheme of the NCEP mesoscale Eta model.
Boundary-Layer Meteor., 85, 391-421
REFDK= 2.0E-6: a parameter used with REFKDT below to compute sfc runoff parameter KDT REFKDT = 3.0: surface runoff parameter (nominal range of 0.5 – 5.0)
NOTE: REFKDT is a tuneable parameter that significantly impacts surface infiltration and hence the partitioning of total runoff into surface and subsurface runoff. Increasing REFKDT decreases surface runoff. See next publication:
Schaake, J., V. Koren, Q.-Y. Duan, K. Mitchell, and F. Chen, 1996: Simple water
balance model for estimating runoff at different spatial and temporal scales.
J. Geophysical Res., 101, No. D3.
NOTE: REFDK corresponds to the saturation hydraulic conductivity Ksat for silty clay loam. If the latter parameter value is changed, then REFDK must be equated to that new value.
ZBOT = -8.0 m: nominal depth of TBOT: lower boundary condition on soil temp (range 3-20m) (see discussion of ZBOT in discussion of TBOT in notes below Lines 13 and 23 of Control File in Section 5.0)
SMLOW = 0.5: ‘spread’ factor for SMCWLT
SMHIGH = 3.0: ‘spread’ factor for SMCREF
FXEXP = 2.0: bare soil evaporation exponent (=1 yields linear reduction of bare soil evaporation with decreased soil moisture between SMCMAX and SMCDRY, >1 yields greater-than-linear reduction)
SBETA= -2.0:used to compute veg canopy effect on ground heat flux as a function of greenness CSOIL = 2.00E+6: soil heat capacity (J/m**3/K)
SALP = 2.7.1:shape parameter used in function to infer percent area snow cover from snow depth
CFACTOR = 0.5: exponent used in function for canopy water evaporation
CMCMAX =0.0005 (m): maximum canopy water capacity used in canopy water evaporation FRZK=0.15 a base reference value (for light clay soil type) of parameter for the frozen-soil freeze factor representing the ice content threshold above which frozen soil is impermeable RSMAX=5000 (s/m) maximum stomatal resistance used in canopy resistance routine CANRES TOPT= 298(K) optimum air temperature for transpiration in canopy resistance routine CANRES RTDIS: array specifying vertical root distribution, i.e. the fraction of total root mass present
in each soil layer
Note: RSMAX and TOPT are not yet functions of vegetation class.
Note: Presently, RTDIS is set universally (not dependent on vegetation class) and assumes a uniform root distribution throughout the specified number of root layers for the given
vegetation class.
B) Soil-class dependent parameter arrays (10)
Routine REDPRM applies 9 soil texture classes. These classes are defined near the top of routine REDPRM. The parameters dependent on soil class are:
SMCMAX: maximum volumetric soil moisture (porosity)
SMCREF: soil moisture threshold for onset of some transpiration stress
SMCWLT: soil moisture wilting point at which transpiration ceases
SMCDRY: top layer soil moisture threshold at which direct evaporation from soil ceases DKSAT: saturated soil hydraulic conductivity
PSISAT: saturated soil matric potential
B: the “b” parameter in hydraulic functions
DWSAT: saturated soil water diffusivity
QUARTZ: quartz content, used to compute soil thermal diffusivity
FRZFACT: a parameter used with FRZK to compute the value of parameter FRZX
Note: if soil parameters such as SMCMAX and SMCREF or soil classification scheme are changed, then parameters FRZK and FRZFACT must be changed
C) Vegetation-class dependent parameters arrays (7)
Routine PRMVEG applies the 13 “SiB” vegetation classes. These classes are described in the comment block at the top of routine PRMVEG. The seven veg-class dependent parameters are:
Z0: (m) roughness length
RCMIN (s/m) : minimal stomatal resistance used in canopy resistance of routine CANRES RGL: radiation stress parameter used in F1 term in canopy resistance of routine CANRES HS: coefficient used in vapor pressure deficit term F2 in canopy resistance of routine CANRES LAI: presently set to universal value of 4.0 across all vegetation classes
Note: seasonality of vegetation greenness carried by fraction of green vegetation (SHDFAC) NROOT: number of soil layers from top down reached by roots; note: NROOT ≤ NSOIL SNUP: the water-equivalent snowdepth upper threshold at which
1)100 percent snow cover is achieved for given veg class
2) maximum snow albedo is achieved for given veg class
D) Surface-slope dependent parameter arrays (1)
Routine REDPRM embodies 7 categories of surface slope. These categories are described in a comment block near the top of routine REDPRM. The parameter dependent on slope class is: SLOPE – a coefficient between 0.1-1.0 that modifies the drainage out the bottom of the last
soil layer. A larger surface slope implies larger drainage
E) Classification dimension parameters (3)
Vegetation Types ("SiB-1") after Dorman and Sellers (1989; JAM)
DEFINED_VEG = 13: the number of SiB-1vegetation class categories, assigned as follows:
1: BROADLEAF-EVERGREEN TREES (TROPICAL FOREST)
2: BROADLEAF-DECIDUOUS TREES
3: BROADLEAF AND NEEDLELEAF TREES (MIXED FOREST)
4: NEEDLELEAF-EVERGREEN TREES
5: NEEDLELEAF-DECIDUOUS TREES (LARCH)
6: BROADLEAF TREES WITH GROUNDCOVER (SAVANNA)
7: GROUNDCOVER ONLY (PERENNIAL)
8: BROADLEAF SHRUBS WITH PERENNIAL GROUNDCOVER
9: BROADLEAF SHRUBS WITH BARE SOIL
10: DWARF TREES AND SHRUBS WITH GROUNDCOVER (TUNDRA)
11: BARE SOIL
12: CULTIVATIONS (THE SAME PARAMETERS AS FOR TYPE 7)
13: GLACIAL (THE SAME PARAMETERS AS FOR TYPE 11)
Soil Types after Zobler (1986), except for quartz after Cosby et al (1984)
DEFINED_SOIL = 9: the number of Zobler soil class categories, assigned as follows:
2018年血液透析行业市场调研分析报告
2018年血液透析行业市场调研分析报告
目录 第一节血液透析简介：血液透析是治疗终末期肾病的首选方案 (5) 一、血液透析介绍 (5) 二、血液透析与腹膜透析对比 (6) 第二节全球血液透析行业：发达国家市场成熟，新兴市场快速增长 (7) 一、全球血液透析概况 (7) 二、外资领先企业 (9) 1. 费森尤斯：覆盖透析全产业链的行业龙头 (9) 2. Davita：专注透析服务领域 (11) 第三节国内血液透析市场：近千亿市场潜力，国内公司正崛起 (14) 一、中国血液透析治疗现状和市场规模 (14) 1. 国内血液透析治疗现状 (14) 2. 国内血液透析市场测算 (15) 二、血透治疗费用：打包收费，报销比例逐年提高 (16) 1. 国内血透治疗收费标准 (16) 2. 血透治疗医保报销情况 (16) 三、血液透析产业：外资企业主导，国内公司起步较晚 (17) 1. 血液透析机：进口产品垄断市场 (17) 2. 透析器：血透治疗核心技术，进口产品占据主流 (20) 3. 透析液与管路：市场竞争充分，国内厂商主导 (22) 4. 透析用药：沈阳三生领先EPO市场，低分子肝素是长期趋势 (22) 5. 血液透析服务：政策逐步放开，国内公司跑马圈地 (24) 6. 国内公司崛起之路 (26) 第四节国内透析相关公司分析 (26) 一、威高股份：覆盖透析全产业链的国内龙头 (26) 二、宝莱特：内生+外延打造覆盖血透全产业链 (28) 三、新华医疗：透析服务初具规模 (29)
图表目录 图表1：血液透析原理及过程 (5) 图表2：血液透析与腹膜透析对比 (6) 图表3：国外HD与PD患者治疗结果对比 (6) 图表4：ESRD患者治疗方案比例 (7) 图表5：全球各地区透析患者占比 (8) 图表6：不同地区透析患者数量增长率 (8) 图表7：费森尤斯医疗业务构成 (9) 图表8：费森尤斯医疗透析服务地区分布 (9) 图表9：费森尤斯医疗在透析领域市场份额 (10) 图表10：费森尤斯医疗近年市值变化和主要收购活动 (10) 图表11：Davita业务构成 (11) 图表12：Davita透析服务类型 (12) 图表13：Davita透析服务患者支付来源 (12) 图表14：Da Vita近年市值变化和主要收购活动 (13) 图表15：国内外透析患者治疗率 (14) 图表16：全球部分地区透析患者与人口比率 (14) 图表17：国内在透患者数及增长率 (15) 图表18：国内单次透析治疗费用构成 (16) 图表19：部分省市血液透析收费标准 (17) 图表20：国家关于尿毒症及大病医保支付相关政策 (17) 图表21：费森尤斯透析机 (17) 图表22：2011-2013年进口和国产透析机市场份额 (18) 图表23：国内获批的血液透析机公司及数量 (19) 图表24：透析器原理 (20) 图表25：透析膜材料分类 (21) 图表26：CFDA批准的透析器公司及数量 (22) 图表27：国内EPO市场竞争格局 (23)
市场透析
二、市场透析 1、宏观/微观市场环境分析（政治经济文化技术）国内外行业 政策行业发展现状行业发展趋势机会总结 STP 1)国内保健品发展概况（宏观环境、行业发展状况及趋势） 中国保健品行业兴起于上世纪８０年代，发展至今，经历了几次大起大落。从９０年代初期算起，中国保健品行业大致可划分为几个阶段，每个阶段都以某一类保健品的盛衰作为标志：９２－９３年乌鸡精系列、蜂王浆系列→９５－９６年减肥运动→９８年的养颜美容系列→９９年补钙系列→２００１年送礼系列。 虽然仍面临诸多挑战，但是，中国保健食品产业的发展前景是光明的。在市场需求、技术进步和管理更新的推动下，中国保健品产业发展空间巨大。未来发展将呈现消费者群体多元化、保健品销售模式专营化、宣传模式推陈出新以及保健品成日常消费四大趋势。 2006年中国保健品企业在规模上基本呈现了金字塔的结构，即投资规模在1亿元以上的企业占总数的1.45%，5000万元到1亿元的占12.5%，100万元到5000万元的占6.66%，10万元到100万元的企业最多，占41.39%，而10万元以下的企业为38%。2006年中国医药保健品进出口额突破300亿美元大关，达到306.7亿美元，同比增加20.4%。其中，出口额为196.1 亿美元，同比增加26.3%；进口额为110.6亿美元，同比增长11.2%。（其中的数据用图像语言表达） 目前我国有４０００多家保健食品企业、共７０００多个品牌，还有国外一些实力强大的保健食品生产厂家正伺机进入中国市场。现在已有２０多家世界知名保健品跨国公司，通过收购、兼并、租赁等形式，在中国设立分厂。 政治：国家高度重视药品安全问题，药品安全质量检查力度大大加强，高端市场份额急速增加，保健品品牌化的趋势不可阻挡； 经济：随着社会经济持续、快速、稳定的发展，人们对生活质量、消费结构的要求不断提高，因此，保健品成为了不可忽视的消费点，人们对高档品牌的保健品的追求也不断增加； 文化：随着人们生活水品的提高，人们的文化知识观念不断增强，消费者的自我保护和健康意识也逐渐增强，更加注重产品的质量，所以，高端品牌领域产品的市场发展潜力巨大；
血液透析市场及相关产品
血液透析市场及产品情况简要 一、血液透析基本概述 血液透析（Hemodialysis），临床意指血液中的一些废物通过半渗透膜除去。血液透析是一种较安全、易行、应用广泛的血液净化方法之一。 适应症：(1)急性肾功能衰竭（2）慢性肾功能衰竭（3）急性药物或毒物中毒（4）难治性心衰，肺水肿，肝硬化，肝肾综合症，肾病综合征，电解质紊乱，肝性脑病，高胆红素血症，高尿酸血症，精神分裂症和牛皮癣等也有血透治疗效果。 二、血液透析的市场情况概述 2011年，全球透析人数为215.8万人，同比增长6.4%。未来几年全球透析人数将继续保持6%左右的增长速度，预计到2020年将增长至380万人左右。2011年，全球透析人群仍主要集中在欧美日等发达地区，但是随着发展中国家医保范围的扩大以及国民收入的提高，中国、印度、巴西等国家的透析人数正在快速增长，目前增长率已达10%以上。 2011年，全球血液透析服务市场规模（包括血液透析服务和血液透析设备两部分）约为625亿美元。2012年，中国晚期肾病患者约有200万人，但是由于中国医保报销比例相对较低，中国仅有10~15%的晚期肾衰患者进行透析治疗；随着未来随着中国各级医保覆盖面的逐步扩大，中国晚期肾病患者接受治疗的比例将大幅上升，市场潜力巨大。 晚期肾脏疾病的治疗方案主要包括：肾脏移植，血液透析和腹膜透析。腹膜透析相对血液透析更为便利，费用也更低，但是其洗脱血液中代谢废物的能力较低，且腹膜感染的比例较高；因此目前大部分的透析的患者还是采用血液透析的方式，约占89%（2010年数据）。 全球血液透析设备市场集中度较高，主要由欧美和日本企业占据。2011年，全球透析设备市场前三名生产商分别为德国费森尤斯医疗、美国百特和瑞典金宝。费森尤斯医疗是全球最大的血液透析设备生产商，也是最大的血液透析服务提供者，服务于全球超过23.3万名肾病患者。美国百特是全球最大的腹膜透析设备生产商。 中国血液透析设备主要依赖进口，2012年费森尤斯医疗、瑞典金宝等进口设备在中国血透设备市场占有率达75%左右。中国本土血液透析设备生产企业较少，血液透析机生产企业有广州暨华、重庆多泰、重庆山外山等，透析器生产企业有威高集团、江苏朗生等。由于中国血液透析市场的巨大潜力，多家上市公司涉足透析领域。如华仁药业腹透透析产品已于2012年第三季度全面上市；宝莱特通过收购天津市挚信鸿达医疗器械开发有限公布局血透耗材领域，通过收购重庆多泰医疗设备有限公司取得血液透析机医疗器械注册证；科伦药业通过增资青山利康进入腹膜透析领域等。
平顶山透析市场分析和营销方案
透析市场分析和市场营销策略方案
平顶山透析市场分析和营销策略 一，平顶山透析市场当前现状： 截至2017年底平顶山市辖2个县级市，4区、4个县开设血液透析中心约 17家，总计约470台治疗单元。目前接受透析治疗的患者约1200名。 部分单位血液透析单元和患者数量设备使用率统计 单位患者数量(名) 透析机血滤机床旁机设备使用率使用率排名市场占有率排名矿总： 133 40 4 5 68% 5 11% 2 市一： 112 50 6 1 49% 9 9% 4 市二： 66 27 3 2 52% 6 5,5% 6 市中： 44 26 4 0 37% 10 4% 8 市五： 56 26 2 0 50% 8 5% 7 一五二： 117 26 5 1 94% 1 10% 3 鲁人： 190 50 2 1 90% 2 16% 1 鲁中： 43 13 2 0 72% 4 4% 8 叶一： 70 20 2 0 80% 3 6% 5 叶二： 20 8 2 0 50% 7 2% 9 以上数据显示：①本地区透析市场从行业快速发展阶段已进入到饱 和状态的初步竞争阶段。
②平顶山地区血液透析市场患者治疗需求与医疗资源 配置已经从满足需求阶段逐渐进入到了患者就医治 疗开始拥有主动权，选择权挑选自己满意医疗服务阶 段发展。 ③市区内患者可有多个选择的治疗单位供治疗所需。县 域患者在当地挑选治疗可供选择性小。 ④县域有部分较稳定透析患者群体，多采取就近治疗。 主要竞争单位设备品牌和单次收费价格、月治疗费用 单位透析机品牌单次收费价格（元）平均每周透析次数月治疗费用（元）矿总：金宝/东芝/费森370 8 2960 市一：威高420 8 3360 市二：威高420 8 3360 市五：费森 370 8 2960 市中：威高 405 8 3240 一五二：费森 420 8 3360
透析领域现状与展望
透析领域现状与展望 行业观点 血透市场大爆发，迎来黄金发展期：国家于2012年提出重大疾病医保，并于2013年开始试点，计划于2014年全面实施，其中首推的治疗领域就是尿毒症。经过测算，我国目前接受规范治疗的透析病人仅为30万，到2020年有望接近200万，这对应的是一个价值1000亿的医疗服务细分市场，应该得到投资者的重视。 血透服务是非常优质的商业模式：血透中心连锁的商业模式较传统综合性医院有3点优势：（1）需求极度刚性，经营稳定性很强（2）人均单产较高，管理压力较小（3）投资回报率可观。这几点都为血透服务连锁化发展的复制性提供了有利条件 目前全球有两大血透服务连锁机构费森尤斯和DaVta，两家市值分别达到200和150亿美元，是美国仅次于医院连锁集团HCA的第二大医疗服务板块。 通过“产品+服务”的一体化产业联动进入血透服务市场具有可行性。欧洲输液龙头费森尤斯的发展路径，其率先布局血透相关产品，后进入透析服务市场，并通过产业平台互动实现2块业务共同发展，并驾齐驱的商业模式，这一模式正在被国内相关上市公司所效仿。 一、慢性肾衰竭逐步成为老年慢性病并发症 1、我国慢性肾病患者正快速增加 慢性肾衰竭(chronic renal failure，CRF)是指各种肾脏病导致肾脏的功能渐进性不可逆性减退，直至功能丧失所出现的一系列症状和代谢紊乱所组成的临床综合征。导致慢性肾衰竭的原发性疾病很多，主要包括慢性肾炎、高血压和糖尿病等。 图：慢性肾衰竭原发病占比统计 随着我国老龄社会的到来，高血压、高血糖等疾病的高发导致慢性肾病的发病率持续上升。我国慢性肾病的发病率高达11%，并呈逐年上升趋势；区别
2020年全球血液透析行业市场现状及发展前景分析
2020年全球血液透析行业市场现状及发展前景分析 全球血液透析行业发展现状及前景分析 血液透析又称人工肾，也有人叫肾透析或洗肾。它是血液净化技术的一种。在全世界依赖透析维持生命的上百万患者中多数是血透。血透对减轻患者症状，延长生存期均有一定意义。本文分析了全球血液透析行业发展现状，并对行业市场前景进行了预判。 1、2019年全球约有350万血透患者 费森尤斯2019年年报显示：2019年，全世界约有430万慢性肾功能衰竭患者接受治疗。在这些病人中，大约350万人接受透析治疗，大约81.5万人患有移植肾，约89%分别用血液透析和腹膜透析治疗。弗雷森尤斯医疗中心报告说，家庭血液透析的增长强劲，目前在北美家庭治疗超过25000名患者。主要的增长动力是越来越多的糖尿病和高血压患者常先于慢性肾衰竭发作的病症。
2、2019年全球血透行业市场规模约800亿美元 根据费森尤斯2019年年报中的数据显示，2019年，全球血液透析市场规模约为800亿美元，与2018年同期相比增长4%。
3、2019年全球透析服务市场总值约660亿美元 根据费森尤斯2019年年报中的数据显示，2019年的全球透析服务市场(包含血透药品)总值约为660亿美元，预计2030年全球透析服务的市场规模将达到950亿美元。 欧洲血液透析服务以公立机构为主，而美国和日本以私人运营机构为主。目前全球提供血液透析服务的企业主要有费森尤斯医疗、DaVita、百特等。
根据Fresenius年报数据，2019年全球透析产业中，血透服务市场(包含血透药品)占比82.5%，血透设备和器械市场占比17.5%，透析设备等产品的市场空间不如血透服务市场。
(仅供参考)血透行业情况介绍
血液透析市场行业分析 1.血液透析是透析领域的主导治疗方式 透析疗法是指血液中的一些废物通过半渗透膜排出体外的治疗方法，适用于急、慢性肾衰竭等疾病。一般可分为血液透析（Hemodialysis，HD）和腹膜透析（Peritoneal Dialysis，PD）两种。 血液透析（Hemodialysis，HD） 通过血透机的半渗透膜将ESRD(终末期肾病，End stage renal disease, ESRD，泛指各种慢性肾病的终末阶段，俗称“尿毒症”)患者血液中的代谢物，过量的电解质和水过滤出血液。血液透析的治疗频率是每周2-3次，每次治疗4小时。通常治疗在医院或专门的诊所完成，需要专业护士提供看护。 图一.血液透析治疗方案示意图 腹膜透析（Peritoneal Dialysis，PD） 利用人体自身腹膜的透析功能来滤除血液中的代谢物。因此，腹膜透析不需要透析机。在腹膜透析过程中，透析液通过一根永久植入的导管被引流如腹腔，透析液通过吸收流经腹膜的静脉血中的代谢物，实现透析治疗作用。腹膜透析可分为两种，连续不卧床腹膜透析（CAPD）和自动化腹膜透析（APD）。CAPD要求患者每天四次手冻更换腹腔中的透析液；APD则通过透析机器自动更换透析液，实现在晚间患者入睡时进行透析治疗。
图二.腹膜透析治疗方法示意图 对于两类疗法，其主要对比如下： 图三.血液透析和腹膜透析治疗的对比 血液投资和腹膜透析对ESRD的临床治疗效果比较上，医学界一直存在争议。腹膜透析从便利性和经费的角度，较血液透析有明显的优势；然而腹膜透析虽然可以在家中自主完成，但由于操作不当和灭菌问题，患者感染腹膜炎的概率较高，一旦感染将极大的影响后续的腹膜透析治疗。 图四.2008年两医院透析患者因并发症门诊和住院情况对比 基于较早的研究资料，在对浙江省两家三甲医院透析治疗效果的临床统计中，腹透者和血透者并发症或感染的年门诊就诊率和住院率存在显著差异，血透者并发症门诊就诊率低于腹透患者。腹透者就诊原因多是腹透炎；血透者就诊疾病主要是感染。 世界各国/地区在选择ESRD的治疗方式上存在巨大差异，然而这种差异并不存在明显的人种和地域集群特征。当然血透由于更高的治疗安全性，在大多数发达过程成为主流的透析治疗方式。全球来看采用血液透析与腹膜透析的患者比例大约为9:1。血液透析通过将体内血液引流至体外，经一个由无数根空心纤维组成的透析器中，血液与电解质溶液（透析液）分布在空心纤维内或外，通过弥散/对流进行物质交换，从而清除体内的代谢废物和多余的水分、维持电解质和酸碱平衡。
2017年中国血液透析行业市场竞争格局分析(上海环盟)
2017年中国血液透析行业市场竞争格局分析
2017年中国血液透析行业市场竞争格局分析 (2) 第一节2017年中国血液透析行业竞争现状分析 (2) 第二节2017年中国血液透析行业集中度分析 (3) 一、全球血液透析设备市场集中度分析 (3) 二、血液透析设备行业竞争格局分析 (3) 三、血液透析耗材行业竞争格局分析 (4) 第三节2017-2025年中国血液透析中心发展现状与对策 (4) 一、国外血液透析中心模式 (4) 二、国内血液透析中心发展现状 (5) 三、连锁血液透析中心运营的重点与难点 (6) 1、运营的标准化问题 (6) （1）血液透析中心硬件设施标准化 (6) （2）透析治疗管理标准化 (6) （3）人员培训标准化 (7) （4）自营或合作经营模式的标准化 (7) 2、标准化的实现方法 (7) 3、智能化的管理系统（即IT管理系统） (8) 1
2 2017年中国血液透析行业市场竞争格局分析 第一节 2017年中国血液透析行业竞争现状分析 产业内部的竞争根植于其基础经济结构，并且远远超越了现有竞争者的行为范围。一个产业内部的竞争状态取决于五种基本竞争作用力——进入威胁、替代威胁、买方侃价能力、供方侃价能力、行业内竞争，这些作用力汇集起来决定着该产业的最终利润潜力。一个产业的竞争大大超越了现有参与者的范围。顾客、供应商、替代品、潜在的进入者均为该产业的“竞争对手”，并且依具体情况会或多或少地显露出其重要性。 行业内竞争：现有竞争对手以人们熟悉的方式争夺地位，战术应用通常是价格竞争、广告战、产品引进、增加顾客服务业务。发生这种争夺或者因为一个或几个竞争者感到有压力，或者因为它们看到了改善自身处境的机会。在大多数产业中，一个企业的竞争行动对其竞争对手会产生显着影响，因而可能激起竞争对手们对该行动进行报复或设法应付。 图表- 1：中国血液透析行业环境“波特五力”分析模型 国内单次透析费用约500-600元，包括耗材（管路、透析液）、透析器、药品（EPO 、肝素）以及服务费、监护费、折旧费等。其中透析器是整个透析治疗进入威胁 卖 方 侃 价 能 力 买 方 侃 价 能 力 替代威胁 血液透析行业内竞争
国内血液透析市场浅析
国内血液透析市场浅析 众所周知，血液透析市场可以划分为设备和耗材2个细分领域，具体的说就是透析机、透析器、透析导管、透析管路、透析液和透析粉5大类，其中透析液和透析粉可以归属为同一大类。 根据《2011-2015年中国血液透析行业发展前景与投资前景深度研究报告》的数据统计，目前全世界透析患者人数约250万人左右，中国透析患者人数约25万人；到2020年，这个数字将超过350万，目前国内血透市场规模已超过100亿元。 目前中国的血液透析设备主要是国外进口品牌为主，有德国的费森尤斯、贝朗、瑞典的金宝和日本的东丽、尼普洛、旭化成、日机装等。据医疗网数据监测了解，进口品牌占有率超过70%的市场份额，国内目前仅有5家企业占有剩下的市场份额。 在血液透析耗材领域，国内企业做的最好的是透析液和透析粉这个细分行业，国产品牌在这个细分行业能占到90%以上的市场份额。国产品牌正逐步替代进口品牌，其中血液透析器中的80%、血液透析管路中的50%、血液透导管中的75%市场份额属于进口品牌。 血液透析粉和透析液以国内品牌为主，在全国有20多家企业可以生产透析液和透析粉产品，主要分布在天津、广东、江苏、河北和辽宁等地区。血液透析液和透析粉属于国家 III类医疗器械注册产品，产品的生产和销售主要受原材料和物流成本等因素影响。目前国内市场主要以透析液为主，透析液与透析粉的市场份额比例大约6:4。 国内有血液透析业务的上市公司有广东宝莱特、华仁药业、华润双鹤和科伦药业等企业。其中广东宝莱特医用科技股份有限公司我们可以重点关注一下，该公司在血液透析领域接连开展一些大动作： 2012年5月，宝莱特收购天津市挚信鸿达医疗器械开发有限公司（透析液、透析粉），持有挚信鸿达60%股权； 2013年1月，宝莱特收购重庆多泰医用设备有限公司（透析机），持有重庆多泰100%股权； 2013年6月，宝莱特收购辽宁恒信生物医用设备有限公司（透析液、透析粉），持有恒信生物100%股权； 2013年8月，宝莱特发布公司公告称，拟在天津投资6,500万元设立独资子公司天津宝莱特医用科技有限公司，负责透析液、透析粉业务。