Salinity and temperature nudging - Revision history

Yjzhang at 17:28, 18 December 2014

2014-12-18T17:28:26Z

Yjzhang at 14:23, 14 February 2013

2013-02-14T14:23:30Z

Eli: /* Formulation */

2013-02-12T20:44:57Z

‎Formulation

Eli: /* Salt and Temperature Nudging in SELFE */

2013-02-12T20:43:34Z

‎Salt and Temperature Nudging in SELFE

Eli at 20:06, 12 February 2013

2013-02-12T20:06:49Z

Eli at 20:05, 12 February 2013

2013-02-12T20:05:34Z

Eli at 18:28, 12 February 2013

2013-02-12T18:28:15Z

Eli at 18:27, 12 February 2013

2013-02-12T18:27:45Z

Eli at 18:25, 12 February 2013

2013-02-12T18:25:07Z

Eli at 18:22, 12 February 2013

2013-02-12T18:22:11Z

@@ Line 1: / Line 1: @@
-== Salt and Temperature Nudging in SELFE ==
+== Salt and Temperature Nudging in SCHISM==
 '''Note: This entry only covers salt and temperature, although similar types of nudging are also available for hydrodynamic variables and tracers.'''
 Salt and temperature nudging is available by means of analysis nudging (Newtonian relaxation). The nudging allows the model state to be reconciled with observations in four dimensions. There are three known examples of this nudging:
 * CORIE applications on the Columbia River, assimilating NCOM results near the ocean boundary
-* The SESAME project, using nudging to couple ROMS on the California coast and SELFE on the San Francisco Bay-Delta in a common band along the coast. In this case velocity was also nudged.
+* The SESAME project, using nudging to couple ROMS on the California coast and SCHISM on the San Francisco Bay-Delta in a common band along the coast. In this case velocity was also nudged.
 * Salinity initialization of the Bay-Delta project, which uses salt nudging to shorten long spin up times far upstream of the ocean boundary
@@ Line 12: / Line 12: @@
 \frac{\partial \alpha}{\partial t} = F(\alpha,x,t) + W_{\alpha}(x,t)(\hat{\alpha_0} - \alpha)
 $$
-where $\alpha$ comprises the state variables to be nudged, $\hat{\alpha_0}$ are the analysis data to be assimilated, $F()$ represents the ordinary SELFE dynamics and the $W_\alpha$ are relaxation weights that are in turn the product of horizontal and vertical contributions:
+where $\alpha$ comprises the state variables to be nudged, $\hat{\alpha_0}$ are the analysis data to be assimilated, $F()$ represents the ordinary SCHISM dynamics and the $W_\alpha$ are relaxation weights that are in turn the product of horizontal and vertical contributions:
 $W_{\alpha} = w_{xy} \cdot w_{z}$

@@ Line 21: / Line 21: @@
 === param.in ===
-;inu_st: Enables nudging for inu_st = 1.
+;inu_st: Enables nudging for inu_st = 2 (if inu_st=1, the state is nudged to i.c. and no *_nu.in are needed).
-;step_nu: This is the nudging data time step, the rate at which new data are introduced to the model. It should be a multiple of the model time step. Nudging is performed every time step, through the entire simulation. Between data time steps, data is linearly interpolated.
+;step_nu: This is the nudging data time step, the rate at which new data are introduced to the model. It needn't be a multiple of the model time step. Nudging is performed every time step, through the entire simulation. Between data time steps, data is linearly interpolated.
 ;vnh1, vnh2, vnf1, vnf2: These are parameters used to compose $w_z$ composing the relaxation weights. For a model location between the surface and depth of vnh1, vnf1 is used. Deeper than vnh1 but less than vnh2, the weight is interpolated between vnf1 and vnf2. At depths greater than vnh2, vnf2 is used.
@@ Line 31: / Line 31: @@
 === salt_nu.in and temp_nu.in ===
-These files contain the actual data used for the nudging. Nudging data are given for all nodes, not the locations of observations, and the analysis of data is assumed precalculated. The analysis quality of locations (ie lower far from any good observations) would thus be handled by:
+These files contain the actual data used for the nudging. Nudging data are given for all nodes, not the locations of observations, and the analysis of data is assumed precalculated. The analysis quality of locations (i.e. lower far from any good observations) would thus be handled by:
 .       a low assignment in the horizontal weight, probably with finite support so there are many zeros in this file
 .       an arbitrary value in salt_nu.in.
@@ Line 39: / Line 39: @@
           open(35,file='salt_nu.in',form='unformatted')
           do istep=0,nsteps
-            write(35)istep*dt_nu     ! time stamp in sec (starting from 0)
+            write(35)istep*step_nu     ! time stamp in sec (starting from 0)
              do inode=1,np           ! all nodes
-                write(35)(saltout(jvert,inode),jvert=1,nvrt)   ! all vertical layers
+                write(35)(salt_nu(jvert,inode),jvert=1,nvrt)   ! all vertical layers
              enddo
            enddo
 </nowiki>

@@ Line 15: / Line 15: @@
 $W_{\alpha} = w_{xy} \cdot w_{z}$
-The horizontal, vertical and time parameters for the model are described below. Observation quality and the global nudging factor are bundled into $w_{xy}$. Time weighting is constant, though data are linearly interpolated between observations.
+The horizontal, vertical and time parameters for the model are described below. Observation quality is bundled into $w_{xy}$. Time weighting is constant, though data are linearly interpolated between observations.
 == Files and Parameters ==

@@ Line 1: / Line 1: @@
 == Salt and Temperature Nudging in SELFE ==
-'''Note: This entry only covers salt and temperature, although similar types of nudging is also available for hydrodynamic variables and tracers.'''
+'''Note: This entry only covers salt and temperature, although similar types of nudging are also available for hydrodynamic variables and tracers.'''
 Salt and temperature nudging is available by means of analysis nudging (Newtonian relaxation). The nudging allows the model state to be reconciled with observations in four dimensions. There are three known examples of this nudging:

@@ Line 12: / Line 12: @@
 \frac{\partial \alpha}{\partial t} = F(\alpha,x,t) + W_{\alpha}(x,t)(\hat{\alpha_0} - \alpha)
 $$
-where $\alpha$ comprises the state variables to be nudged, $F()$ represents the ordinary SELFE dynamics and the $W_\alpha$ are relaxation weights that are in turn the product of horizontal and vertical contributions:
+where $\alpha$ comprises the state variables to be nudged, $\hat{\alpha_0}$ are the analysis data to be assimilated, $F()$ represents the ordinary SELFE dynamics and the $W_\alpha$ are relaxation weights that are in turn the product of horizontal and vertical contributions:
 $W_{\alpha} = w_{xy} \cdot w_{z}$