1. Recent developments in Latent Heat Nudging at DWD
Stefan Klink, Klaus Stephan and Christoph Schraff
“blacklist” for radar data
latent heat nudging and “prognostic” precipitation
results of assimilation experiments
summary and aspects of future work

2. “Blacklist” for radar data
Motivation: detection of ground clutter, which is not removed by the operational Doppler filter,
clutter occurs at many of these grid points more or less permanently
total sum of precipitation derived from the DX radar composite
Again, hourly accumulated precipitation height is plotted in the figures.
The LHN run with diagnostic precipitation shows precip patterns, which are in good agreement both in position and amplitude with the radar observations.
When we look at the run with prognostic precipitation, we detect, that too much precipitation is inserted during the assimilation and that further on the horizontal structure of precipitation no longer fits so well to the Radar.
approach: consistency of radar derived precipitation rate and satellite derived cloud-type product (Met-8 Nowcasting-SAF) at each grid point over a longer time period (e.g. 15 days)
blacklist criterion: at 20% of the cloud-free dates, a non-zero precipitation rate has to be found at this special grid point
Usage during assimilation: blacklisted grid points are not treated by the LHN-algorithm
Plan: update this mask once a month, taking at least the last 30 days into consideration

3. Again, hourly accumulated precipitation height is plotted in the figures.
The LHN run with diagnostic precipitation shows precip patterns, which are in good agreement both in position and amplitude with the radar observations.
When we look at the run with prognostic precipitation, we detect, that too much precipitation is inserted during the assimilation and that further on the horizontal structure of precipitation no longer fits so well to the Radar.

4. Hourly accumulated precipitation height
Again, hourly accumulated precipitation height is plotted in the figures.
The LHN run with diagnostic precipitation shows precip patterns, which are in good agreement both in position and amplitude with the radar observations.
When we look at the run with prognostic precipitation, we detect, that too much precipitation is inserted during the assimilation and that further on the horizontal structure of precipitation no longer fits so well to the Radar.

5. test case with “prognostic” precipitation
Again, hourly accumulated precipitation height is plotted in the figures.
The LHN run with diagnostic precipitation shows precip patterns, which are in good agreement both in position and amplitude with the radar observations.
When we look at the run with prognostic precipitation, we detect, that too much precipitation is inserted during the assimilation and that further on the horizontal structure of precipitation no longer fits so well to the Radar.
Hourly accumulated precipitation height

6. “Prognostic” Precipitation
diagnostic
prognostic
just a diagnostic expression for the precipitation flux :
full prognostic equation for the mass fraction :
precipitation falls immediately and in the same column, in which it has been formed.
t = 0 ; xy = 0
precipitation falls with a certain sedimentation velocity through the model space and could be advected horizontally , too.
t > 0 ; xy  0

7. Latent heat nudging and “prognostic” precipitation
LHN-Assumption: vertically integrated latent heat release  precipitation rate
55km y x
The correlation between the vertically integrated rate of latent heat release and the surface precipitation rate is significantly smaller in the simulation with prognostic precipitation

8. Integration within one column Integration along a path
The precipitation rate reflects the integral of latent heat release along the path of precipitation particles through the atmosphere from the formation of cloud droplets
until the contact with the ground.
diagnostic
prognostic
Integration within one column
Integration along a path

9. main part of positive latent heat release occurs in updrafts,
strong precipitation rates are often related to downdrafts
at x < 3 km , with prognostic treatment of precipitation (model resolves large clouds):
model is able to distinguish between updrafts and downdrafts inside convective systems
horizontal displacement of areas with strong latent heating resp. to surface precipitation,
modified spatial structure of latent heat release in the model
scheme will notice only with temporal delay if precipitation already activated by LHN + -
from:
R. A. Houze, Jr.:
Cloud Dynamics
International
Geophysics
Series Vol. 53

10. possible adaptations I
horizontal displacement of vertically integrated latent heating and surface precip.:
 strong horizontal smoothing applied to 2D fields of observed and modelled surface precipitation rate and to 3D field of latent heat release, in order to get higher correlation of precipitation and latent heating
(is found to have limited impact, tends to decrease precipitation amounts)

11. possible adaptations II
change of the spatial structure of latent heat release in the model:
updraft regions (at the leading edge of a convective cell): very high values of latent heat release, little precipitation
higher values of the scaling factor 
and of LHN increments often occur
reduce upper limit of the scaling factor
adapt grid point search routine
downdraft regions (further upstream): high precipitation rate, weak latent heat release (often negative in most vertical layers)
LHN increments are inserted only in the vertical layers where the model latent heating rates are positive (approx. in cloudy layers)
(to avoid e.g. negative LHN increments and cooling where the precipitation rate should be increased)

12. possible adaptations III:
temporal delay effect (generated precipitation reaches the ground with some delay):
 an immediate reference information, on how much precipitation the temperature increment has initialised already, is required within each time step
use of a ’reference precipitation’ RRref:
diagnostically calculated precipitation rate (by additional call of diagnostic precipitation scheme without any feedback
on other model variables)
vertically averaged precipitation flux
(more consistent, however it does not eliminate the temporal delay completely)
for LHN: temporal delay effect found to be much more important than spatial displacement

13. Experiment for 07 – 18 July 2004 (mainly convective precipitation events)
Model setup:
general settings
LM version 3.13
LMK configurations (2-TL-scheme, SL advection scheme)
continuous assimilation cycle, 00-, 12-, 18- UTC forecasts
LHN experiment
‘undelayed’ reference precipitation (vertically averaged precipitation flux)
applying temperature increments ‘only in clouds’
upper limit of scaling factor = 2, lower limit = 0.5
analysed 3D precipitation fields not passed to the forecasts
laterally nested into GME
CTRL experiment
laterally nested into LM

14. Hourly accumulated precipitation height

15. Hourly accumulated precipitation height

16. Hourly accumulated precipitation height

17. 12 UTC forecasts, ETS precipitation (hourly heights), threshold values: 0.1, 0.5, 1.0, 5.0 mm

18. Assimilation, FBI precipitation (hourly heights), threshold values: 0
Assimilation, FBI precipitation (hourly heights), threshold values: 0.1, 0.5, 1.0, 5.0 mm
0.1
0.5
1.0
5.0

19. Experiment for 07 – 18 July 2004 (mainly convective precipitation events)
Model setup:
general settings
LM version 3.15
new LMK configurations (2-TL-scheme, Bott advection scheme)
continuous assimilation cycle, 00-, 12-, 18- UTC forecasts
LHN experiment
‘undelayed’ reference precipitation (vertically averaged precipitation flux)
applying temperature increments ‘only in clouds’
upper limit of scaling factor = 1.7, lower limit = 0.3, + logarithmic scaling
analysed 3D precipitation fields passed to the forecasts
laterally nested into LM
CTRL experiment
result of a 4-day intermediate experiment:
FBI for 5.0 mm threshold during assimilation
(LM 3.13, nested into GME):
revised version decreases overestimation of
precipitation compared to previous LHN version

20. assimilation 0.1 mm 2.0 mm ETS FBI threshold values
scores for hourly precipitation : with latent heat nudging / without latent heat nudging
assimilation
0.1 mm
threshold values
2.0 mm
ETS
FBI

21. … and similar results for 18-UTC forecasts
scores for hourly precipitation : with latent heat nudging / without latent heat nudging
12-UTC forecasts
0.1 mm
threshold values
2.0 mm
ETS
FBI
… and similar results for 18-UTC forecasts

22. … and similar results for 18-UTC forecasts
scores for hourly precipitation : with latent heat nudging / without latent heat nudging
18-UTC forecasts
0.1 mm
threshold values
2.0 mm
ETS
FBI
… and similar results for 18-UTC forecasts

23. 0-UTC forecasts 0.1 mm 2.0 mm ETS FBI threshold values
scores for hourly precipitation : with latent heat nudging / without latent heat nudging
0-UTC forecasts
0.1 mm
threshold values
2.0 mm
ETS
FBI

24. dashed: with latent heat nudging / solid: without latent heat nudging
verification against German radiosondes, 11-day period (8 – 18 July 2004):
dashed: with latent heat nudging / solid: without latent heat nudging
bias
+ 0 h
+ 6 h
+ 12 h
+ 18 h
drier
moister
relative
humidity
temperature
more
stable
colder

25. dashed: with latent heat nudging / solid: without latent heat nudging
verification against German radiosondes, 11-day period (8 – 18 July 2004):
dashed: with latent heat nudging / solid: without latent heat nudging
r m s e
+ 0 h
+ 6 h
+ 12 h
+ 18 h
r e l a t I v e h u m I d I t y
t e m p e r a t u r e
worse
better

26. Summary of Results
‘blacklist’ for radar data: avoids introduction of spurious rain at radar locations
several adaptations to LHN to cope with prognostic precipitation; most important:
use of an ‘undelayed’ reference precipitation (vertically averaged precipitation flux)
revised LHN, assimilation mode:
simulated rain patterns in good agreement with radar observations,
overestimation of precipitation strongly reduced
strong gravity waves induced  LHN forcing too strong (?)
subsequent forecasts, impact on precipitation (10-day summer period):
large positive impact for 4 hours (longer than in simulations with diagnostic precip)
mixed ETS impact beyond + 6 h (interpretation yet unclear,
need verification without ‘double penalty’)
frequency bias slightly improved, increased values from + 0 h to + 6 h,
slightly decreased values from + 6 h to h
upper-air verification (11-day summer period):
LHN cools and dries PBL, increases mid-tropospheric stability and upper-tropospheric moisture
overall neutral impact on rmse of forecasts, temperature improved in PBL at + 6 h
moderately degraded around 700 hPa later on

27. Aspects of Further Work
more case studies for both summer and winter periods (up to 10 days),
(further problems ?)
further diagnosis of LHN results,
in order to better understand some problems (e.g. performance of 0-UTC runs, decrease of forecast impact, too strong LHN forcing) and improve / tune LHN scheme
role of gravity waves
vertical structure of precipitating cells (e.g. wind field)
vertical distribution of LHN increments
environment of precipitation cells (moisture convergence)
horizontal filtering
introduction of PI-data (international composite) outside the German DX-area
further use of cloud type product of Nowcasting-SAF within LHN (humidity adjustment)
LMK test suites (periods up to three months), with comprehensive verification
( possibly: use of 3D reflectivity data in order to determine more precisely (both in space and time)
the areas of positive latent heat release
height-dependent scaling of the latent heat rate )

29. Prognostic Precipitation and LHN - Influence on LHN
spec. cloud water
spec. cloud ice
latent heat rate
spec. rain content
spec. snow content

30. Possible adaptations: Adjusting the controlling LHN parameters
Applying of the temperature increment only in certain layers
Adaptation of the grid point search routine
Spatial Averaging of precipitaion patterns and the pattern of latent heat release
Spatial displacement of radar image
Use of an undelayed precipitation rate as reference for the LHN
diagnostically calculated precipitation rate
vertical integration of the precipitation fluxes