PL-TR-94-219 AD-A286 638IlI~lU|~l~i|hE

REAL-DATA TESTS OF A SINGLE-DOPPLERRADAR ASSIMILATION SYSTEM

Thomas NehrkornJames HegartyThomas M. Hamil

Atmospheric and Environmental Research, Inc.840 Memorial DriveCambridge, MA 02139

June 30, 1994 1EL T (7,0V,1.51994,

Scientific Report No. 5

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June 1994 Scientific No. 5

4. TITLE AND SUBTITLE S. FUNDING NUMBERSReal-Data Tests of a Single-Doppler Radar Assimilation F19628-91-C-oo11

SystemPE 62101F

6. AUTHORt(S) PR 6670 TA 17

Thomas Nehrkorn, James Hegarty, Thomas M. Hamill WU CA

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13. ABSTRACT (Maxifum 200 words)

Real data tests of a single-Doppler radar data assimilation and forecast system have been conducted for aFlorida sea breeze case. The system consists of a hydrostatic mesoscale model used for prediction of thepreconvective boundary layer, an objective analysis that combines model first guess fields with radarderived horizontal winds, a thermodynamic retrieval scheme that obtains temperature information from thethree-dimensional wind field and its temporal evolution, and a Newtonian nudging scheme for forcing themodel forecast to closer agreement with the analysis. As was found in earlier experiments with simulateddata, assimilation using Newtonian nudging benefits from temperature data in addition to wind data. Thethermodynamic retrieval technique was successful in retrieving a horizontal temperature gradient from theradar-derived wind fields that, when assimilated into the model, led to a significantly improved forecast ofthe seabreeze strength and position.

14. SULIECT TERMS IS. NUMBER OF PAGES

Convection Seabreeze 56Single Doppler Radar Thermodynamic Retrieval 16. PRICE CODE

17. SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LIMITATION OF ABSTRACTOF REPORT OF THIS PAGE OF ABSTRACT

Unclassified Unclassified Unclassified SAR

NSN 7S40-01-280-5500 Standard Iorm 298 (Rev 2-89)P,ec.,bd V ANA %ld I IS.16298 tt0

Tabl of Contents

1. Introduction .............................................................................................. 12. The Prototype Assimilation and Forecast System .................................... 2

2.1. The m esoscale forecast m odel ............................................................. 22.2. Radial w ind extraction (SPRINT) ..................................................... 32.3. Radial and tangential wind extraction (TREC) ............................... 32.4. Objective analysis of w inds ............................................................... 42.5. Therm odynam ic retrieval .................................................................... 52.6. N ew tonian nudging ............................................................................ 7

3. Case Selection ............................................................................................... 73.1. General rem arks ................................................................................... 7

3.2. The 23 July case ................................................................................... 94. Assim ilation Experim ents ............................................................................ 11

4.1. General rem arks .................................................................................. 114.2. Control run ........................................................................................... 114.3. W ind-only assim ilation ....................................................................... 134.4. W ind and tem perature assim ilation ................................................... 15

5. Sum m ary and Conclusions ......................................................................... 17

6. References ....................................................................................................... 18

Aoeession Fo•

DTIC

By

iii 4 i

Ust of RiaumEl

1 Plots of PAM surface data. Station locations correspond to theorigin of the wind vectors; potential temperature is plotted aboveand to the left of the station location .......................................................... 20

2 TREC derived winds valid for 1705 UTC, over the same geographic

region and with the same wind vector scale as in Figure 1, forelevation angles 0.30, 0.90, 1.50, and 2.1 ............................1........................ 24

3 Fractional area of PL-3D gridpoints covered by water. Modeldomain shown corresponds to the area plotted in Figure 1 ..................... 26

4 The sounding used to initialize the model runs: potentialtemperature - top panel, u (solid) and v (dotted) - bottom panel ............ 27

5 Horizontal cross section of winds and 0 at level 2, and vertical crosssection at y--O, for hour 2 (16 UTC) of the control run .............................. 28

6 Horizontal cross section of winds and 0 at level 2, and vertical crosssection at y=0, for hour 4 (18 UTC) of the control run .............................. 29

7 Horizontal cross section of winds and 0 at level 2, and vertical crosssection at y=O, for hour 6 (20 UTC) of the control run .............................. 30

8 Horizontal cross sections of winds and 0 at level 4 for hours 2, 4, and6 (16, 18, and 20 UTC) of the control run ...................................................... 31

9 Vertical cross section of winds and 0 at y=+25 km, for hours 2, 4, and

6 of the control run . ....................................................................................... 3310 Horizontal cross section of winds and 0 at level 2 for hour 3 (17

UTC) of the wind-only assimilation: first guess, analysis, andanalysis increm ents ........................................................................................ 35

11 Horizontal cross section of winds and 0 for level 2 at hour 4 (18UTC): wind-only assimilation and differences from control .................. 37

12 Vertical cross section of winds and 0 at y--O for hour 4 (18 UTC):wind-only assimilation and differences from control ............................... 38

13 Horizontal cross section of winds and 0 at level 2 for hour 6 (20UTC): wind-only assimilation and differences from control .................. 39

iv

Lit of FigurM (€ontInued) EM

14 Vertical cross section of winds and 0 at y=O for hour 6 (20 UTC):

wind-only assimilation and differences from control .............................. 4015 Horizontal cross section of winds and 0 at level 2 for hour 3 (17

UTC) of the full assimilation: first guess, analysis, and analysis

increm ents ....................................................................................................... 4116 Horizontal cross section of winds and 0 at level 4 for hour 3 (17

UTC) of the full assimilation: first guess, analysis, and analysis

increm ents ....................................................................................................... 4217 Horizontal cross section of winds and 0 at level 2 for hour 4 (18

UTC): full assimilation and differences from control ............................... 4318 Horizontal cross section of winds and 0 at level 4 for hour 4 (18

UTC): full assimilation and differences from control ............................... 4419 Vertical cross section of winds and 0 at y--O for hour 4 (18 UTC): full

assimilation and differences from control ................................................... 4520 Horizontal cross section of winds and 0 at level 2 for hour 6 (20

UTC): full assimilation and differences from control ............................... 4621 Horizontal cross section of winds and 0 at level 4 for hour 6 (20

UTC): full assimilation and differences from control ................... 4722 Vertical cross section of winds and 8 at y=0 for hour 6 (20 UTC): full

assimilation and differences from control ................................................... 48

23 Horizontal cross section at level 2, and vertical cross section at y--0,of winds and 0 for hour 6 (20 UTC): differences between fullassimilation and wind-only assimilation .................................................. 49

v

1. Inltroduction

This technical report is the last report in a series of three reports describingour research into the feasibility of thunderstorm prediction based on thecontinuous assimilation of single-Doppler radar information into a numerical

forecast model. This research is motivated by several factors: the introduction of

the WSR-88D (formerly called NEXRAD) network of single Doppler radarsmakes this data source widely available; the onset of convection has been linked

to low-level convergence (Wilson and Schreiber, 1986); and dear-air returns from3-5 cm radars in the preconvective boundary layer (from seeds and insects) aresufficient to allow determination of radial velocities (Kropfli, 1986). Theapproach taken in our research was to use a simple, hydrostatic mesoscale modelto predict the evolution of the boundary layer, and to assimilate single-Dopplerradar observations into the model to improve the forecast. Nowcasts andforecasts from the mesoscale model could then be used to identify present andfuture regions of boundary layer convergence, which would be areas of

preferential thunderstorm initiation. We concentrated on the Florida sea breezein our work, because of the well-established success of mesoscale models insimulating the sea breeze, and the availability of data from the Convection andPrecipitation/Electrification (CaPE) experiment conducted over Florida in 1991.

The first report in the series (Hamill, 1992) describes the forecast model usedin this study (PL3D - a hydrostatic version of the Colorado State UniversityRegional Atmospheric Modeling System (CSU RAMS)) and the results ofobserving system simulation experiments demonstrating the importance ofassimilating wind and temperature data, rather than just wind data. Thisconfirmed the results by Liou (1989) and Cotton et al. (1989) that assimilationusing Newtonian nudging (Stauffer and Seaman, 1990) of the observed Doppler

wind velocities alone is usually insufficient; temperature information is alsoneeded. Without temperature information, circulation patterns developed fromthe assimilation of wind data may not be sustained. In the preconvectiveboundary layer, areas with low-level convergence are usually also areas with

positive buoyancy. As was shown in Cotton et al. (1989), nudging the windsalone in this situation may actually create a cold anomaly through adiabaticcooling, resulting in the circulation reversing direction after the nudging isstopped. Our own assimilation experiments using wind data alone (Hamill,

1992) for a seabreeze simulation also showed generally inferior forecastscompared to those experiments with nudging to observed winds andtemperatures.

The approach taken in our research is to "retrieve" atmospheric temperaturesfrom the measured wind field. Provided the winds are known with reasonableaccuracy, the temperature field can be deduced from the three-dimensional

distribution of the wind field and its temporal evolution, because the two arelinked through the equations of motion (Gal-Chen, 1986). Because singleDoppler radar measurements only provide the radial component of the wind, wehave designed a multi-step prototype forecast and assimilation system. The first

step is to extract as much information as possible about the 3-D windflow from asingle-Doppler radar using two algorithms, one of which produces observationswith not only radial but also tangential wind velocities. Both types of Doppler-derived observations are then combined with a model forecast through a simple

objective analysis and the resultant wind analyses drive the Gal-Chen tempera-ture retrieval. With high-resolution analyzed fields of wind and temperature, the

simple mesoscale model forecast is then nudged toward a more realisticdescription of the atmosphere, presumably resulting in a more realistic forecast.

The second technical report (Hamill and Nehrkorn, 1993) describes ourimplementation of this technique, and results from tests with simulated data. In

this report we describe tests of our prototype system with real data. We brieflyreview the assimilation procedure in Section 2, but for a more detaileddescription the reader is referred to Hamill and Nehrkom (1993). The caseselection from the CaPE experiment data is described in Section 3, the results ofthe assimilation experiments are described in Section 4, and Section 5 contains a

summary and conclusions.

2. The Prototvpe Assimilation and Forecast System

2.1. The mesoscale forecast model

The PL-3D mesoscale model is a modified, hydrostatic version of the CSURAMS (Tripoli and Cotton, 1982). It is described fully in Gustafson et al. (1991)and Cotton et al. (1989) , and references contained therein. Its governingequations are the hydrostatic equations of motion, with prognostic variables u, v,and 0 (horizontal wind and potential temperature). Thermodynamic variables

2

are decomposed into a horizontally uniform, time-invariant basic state, anddeviations from this state. The pressure field (in the form of the Exner function 1)is diagnosed from the hydrostatic equation, and the vertical velocity from theanelastic continuity equation where only variations of the basic-state density are

considered. It includes a first-order turbulence closure where diffusioncoefficients are a function of the vertical deformation and the Richardsonnumber, a soil heat transfer parameterization, and a radiation package thatallows a simulation of the planetary boundary layer. Water vapor is treated as apassive tracer only in this version and moist processes (condensation andprecipitation physics) are ignored. It uses a staggered grid in the horizontal andvertical and allows for a terrain-following vertical coordinate, though a flatterrain is used in these simulations. The equations are solved with a time-split

scheme, which uses a smaller time step for terms which admit the fast Lambwave. Advective terms are computed using a second-order accurate forward-in-

time upstream advective operator.

2.2. Radial wind extraction (SPRINT)

The SPRINT (Sorted Position Radar INTerpolation) software, developed atthe National Center for Atmospheric Research, performs a Cartesian rectification

of Doppler measurements (Mohr et al., 1986). It is used to grid the Dopplerradial velocities at regular time intervals, making them available to the objectiveanalysis software. SPRINT software is typically used in the gridding of dual-Doppler data; however, for our purposes it was used to grid single-Dopplerradial wind components. The SPRINT software was obtained from NCAR andinstalled on the Cray-YMP of the Army Waterways Experiment Site (WES). Theoutput format was modified to facilitate the transfer of the data to the AIMSsystem and its ingest by the objective analysis software.

2.3. Radial and tangential wind extraction (TREC)

TREC is the "Tracking of Radar Echoes by Correlation" (Tuttle and Foote,1990). This technique can be used to infer a 2-D wind field from successive scansof measured reflectivities. It does this through a cross-correlation of subsets of a

1For a definition of the Exner function, see Pielke (1984).

3

scan of radar data at time T to all surrounding subsets for a scan at time T+ AT.The displacement vector (i.e., "wind") is from the center of the originating box tothe center of the box with the maximum correlation. This scheme is very useful

because it is currently the only scheme which can derive relatively high-resolu-tion boundary layer wind inferences with both radial and tangential components.However, the TREC scheme is sensitive to ground clutter, works best withclosely timed radar scans (3-5 minutes between successive scans is ideal) andrequires clear-air inhomogeneities or scatterers such as bugs to use as passivetracers. TREC provides information on the movement of features. Features donot necessarily move with the wind. Insect migration and wave propagation cancontribute to the movement of radar features in a direction that differs from thewind. TREC does not provide "wind observations" but, rather, information on

features movement. For clear air situations, the movement of features is perhapsbetter correlated with wind direction than for precipitation situations, but it isimportant to note that the wind interpretation can be in serious error. The TRECsoftware was obtained from the author (John Tuttle, at NCAR) and installed onthe WES Cray-YMP. The code was modified to change output format and thegraphical output routines were moved to a stand-alone program to be run on theAER computer system.

2.4. Objective analysis of winds

This step adjusts a model first guess of the wind field to wind velocityobservations from TREC and gridded radial velocities from SPRINT. Thisobjective analysis is based on the technique of successive corrections (Cressman,1959), but differs in some substantive ways from the basic Cressman scheme.The major differences are as follows:

a. Analysis in radial/angental coordinate system. It is traditional toperform the objective analysis on the u- and v-components of the wind. With thecurrent code, the analysis is done on radial and tangential components and

converted back to u/v as a last step. This is done because the TREC schemesupplies observations with both a radial and tangential component, but theSPRINT output has only radial velocities. Analyzing in the conventional u/vcoordinate system would require a prior step of inferring some tangentialcomponent of the wind for the SPRINT observations - a step liable to induceerror.

4

b. Use of only one SPRINT observatior. For the SPRINT observations, onlythe derived radial velocity at a particular gridpoint is allowed to affect theanalysis at that gridpoint; neighboring gridpoints' radial velocities are not used.Once again, this is due to the incomplete wind information having only radialvelocities. Nearby gridpoints, especially close to the radar, will have a radialdirection different from the radial direction at the analysis point; thus, it will nothave complete information on the radial velocity at the original analysis point.

c. Use of nonstandard summation reation. The standard Cressmansummation relation is replaced by one in which the weight given to anobservation is not only a function of horizontal distance between the gridpointand the observation, but also a function of the verticai separation between theobservation and the gridpoint. In addition, weights are computed separately forTREC and SPRINT observations and normalized such that each type ofobservation contributes roughly equally to the analysis. The latter modificationis introduced since only one SPRINT observation is available at a givengridpoint, whereas this gridpoint can be influenced by dozens of TRECobservations. Uncorrected, this could have a deleterious influence on the quality

of the objective analysis.

d. Use of a vertical weighting coefficient. We have developed a verticalweighting coefficient which allows the observation increments to be applied notonly to the level of the observation but to surrounding vertical levels. Thisweight is of the form:

Wv = 1.0 / [1.0+Cv*(Dh)2 ] (1)

where

Wv= derived vertical weight;

Cv = weighting coefficient (m-2); and

D = height difference between observation and analysis level (m).

2.5. Thermodynamic retrieval

Following the method of Gal-Chen (1986) and the derivation of Liou (1989),temperature observations can be derived from gridded wind data. The basicapproach is to rewrite the u- and v-equations such that the x-derivative (y-deri-vative) of pressure is on the left hand side and all other terms of the u-equation(v-equation) are on the right hand side: local time rate of change, horizontal and

5

vertical advection, Coriolis acceleration, and turbulent friction. With the

available Doppler information, we can estimate all the terms on the right hand

side- the horizontal winds are estimated from an objective analysis of Doppler

radar data, the vertical velocities through the procedure described below, and the

local time derivatives through comparisons of successive scans of Doppler wind

analyses. In general, there will be no solution of the pressure field that satisfies

both equations exactly, due to errors in the observational data, approximations of

the governing equations, and their numerical solution. A least squares solutioncan be obtained as the solution of a Poisson equation. The solution, at any

vertical level, is then known only to within an arbitrary additive constant. To

remove this non-uniqueness, we impose the constraint that the horizontal mean

of the derived pressure is equal to that of the model first guess. With the

pressure determined, temperature can be retrieved, as will be shown later.

Specific algorithmic steps in the dynamic retrieval are:

a. alculation of vertical velocity. The PL-3D model normally calculates thevertical velocity from an upward integration of the continuity equation. For

consistency, this was preserved here. However, because Doppler-derived wind

analyses may be noisy, we chose to impose constraints on the diagnosed verticalvelocities. The Doppler-derived vertical velocity was used nearly unchanged

near the grou, 1, but as the model layer height approached a prespecified height

level (Z(km")), it was effectively damped toward that of the first guess.

b. Calculation of u and v forcing functions. The forcing functions (right hand

sides) of the u and v equations must be calculated using the available Dopplerradar data. There are four general terms: the local rate of change, advection,

coriolis, and turbulence. Existing CSU/RAMS code is used to calculate all terms

except the local rate of change, which is calculated using a backward differencewith the previous analysis.

c. Dmic Retrieval of Pressure Perturbations. Using standard numerical

techniques such as sequential over-relaxation (Vemuri and Karplus, 1981) thePoisson equation for pressure is solved level by level. Layer mean temperatures

are then computed from the analyzed pressure at surrounding analysis levels.

6

d. Extractin of Tempe ture Observaions. The hydrostatic equation is

written in finite difference form and solved for the mean layer temperatures.Level temperatures are then derived from the layer mean temperatures of the

surrounding layers. A final check is made to ensure that no biases wereintroduced in the vertical interpolation. If necessary, temperatures are reset suchthat their horizontal average is equal to that of the first guess.

2.6. Newtonlan nudging

Following the discussion in Hamil (1992) the model is now nudged to the

new data adjusting the model's time tendencies for u, v, and 0 according to:

Ftot = Fmod + XosXmod) * R * Wt (2)where

Fk* = aX/&t = total local tendency for the gridpoint at a given timestep;Fmod = normal model terms of the local tendency (e.g., advection,

coriolis);X.obs = observed field's value for a gridpoint at time (t);Xmod = model forecast value for a gridpoint at time (t);R = nudging coefficient; and

Wt = weight applied to this timestep.

The residuals (Xobs - Xmod) are calculated at the time when the Doppleranalysis and temperature retrieval are performed and the residual is used untilthe next analysis time. The nudging coefficient (R) used in these experimentswas set at 5.56 x 10-4 51, corresponding to an adjustment time scale of 1800 sec.To deweight the residual as we progress forward in time, Wt starts at 1.0 at thetime of the analysis but decreases, approaching zero right at the time of the nextDoppler analysis and retrieval.

3. Case Selection

3.1. General remarks

Tthf data source for our real data experiments was the CaPE experiment,which was conducted between 8 July and 18 August 1991 over Florida. TheNational Center for Atmospheric Research (NCAR) deployed three radars overthe Cape Kennedy area. The dual wavelength (3 and 10 cm) CP2 radar waslocated at the coast line to the north of Cape Kennedy and used primarily for

7

quantitative measurements of rain, precipitation physics, and cloud electrifica-

tion. A secondary role of the CPL radar was to support aircraft penetration anddual Doppler studies of convective cells. Of more interest for our purpose werethe NCAR CP3 and CP4 radars, which are 5 cm Doppler radars capable ofdetecting air motions in the cloud-free boundary layer. They were located to thesouth of Cape Kennedy, CP4 close to the coast, and CP3 further inland.

Locations of the CP2, CP3, and CP4 radars are indicated in Figure 1 by asterisks.The area shown in Figure 1 is a 160 km by 160 km area centered on the CP4 radar

location, on a Mercator projection. Latitude/longitude scales are shown on theleft/top margins. Also shown are the locations of the NCAR PortableAutomated Mesonet (PAM) surface stations.

To test our prototype assimilation and forecast system, we looked for dayswhich were initially quiescent, and then quickly developed large thunderstormsover the CaPE network, preferably in response to sea breeze forcing.Descriptions of the synoptic situation and the data collection efforts for the

experiment days, contained in the CaPE experiment log (Williams et al., 1992),were reviewed for this purpose. In addition, we obtained video loops of visible

GOES satellite imagery over the Florida area. While reviewing the loops ofvisible satellite imagery, it quickly became apparent that the scenario describedabove was less the rule than the exception. More likely, intense thunderstorm

development was preceded by a more complex series of events. In many cases,small convective clouds did form along the sea-breeze front, but quicklydissipated. More significant thunderstorm development then typically followedfrom the interaction of the outflow boundaries from the initial cells. In one case,27 July, outflow from convection that had formed along the Gulf Coast seabreezeand moved inland forced new, intense convective development when it collidedwith the Atlantic sea breeze front. Simulation and prediction of this series of

events is clearly beyond the capabilities of the simple mesoscale model used inour study and the computational power expected to be available at typicalforecast sites. We did, however, identify one case that fit the selection criteria.On 16 July, intense convection formed along the sea-breeze front, close to theCape Kennedy area, making it a potential case for study.

8

For a closer examination of the radar data, we obtained a software package

from NCAR's Atmospheric Technology Division's Research Branch to peruse and

edit radar data. Examination of the CP2 radar data revealed that for the 16 July

case, during the time for which survey scan data were available, the sea breeze

front was still off-shore and thus not visible due to a lack of scatterers. The CP3

and CP4 data for that day had other problems: there was only one scan

performed at a low enough elevation angle for usable boundary layer returns,

thus making this dataset unusable for the thermodynamic retrieval technique.

Because of the severe constraints on vertical resolution of the radar data in the

boundary layer imposed by the thermodynamic retrieval technique, we

subsequently concentrated on experiment days during which the sea breeze was

sampled well by the CP3 and CP4 radars, even if there was no significant

development on that day along the sea breeze. This led to the final selection of

23 July as our real data test case. The meteorological situation and data coverage

for this day are described in detail in the next section.

3.2. The 23 July case

The synoptic situation, as summarized in Williams et al. (1992), was

characterized by a broad area of high pressure over Florida, with light and

variable winds over the CaPE area. A land breeze existed during the night and

early morning. Thunderstorms were primarily confined to an area well north of

the CaPE area and there was no development in the area covered by the CP3 and

CP4 radars, aside from a cell approximately 40 km to the SSW of CP4, which

developed into a storm by 1946 UTC (1546 EDT).

The development of the seabreeze near Cape Kennedy can be seen from the

sequence of plots of PAM data in Figure 1. At 14 UTC winds are generally light

and variable, although the predominance of the off-shore direction suggests the

presence of a land breeze. Potential temperatures are essentially uniform across

the region aside from an obviously bad data point just south of CP3. One hour

later, temperatures have risen by 1 - 2 K, except right near the coast, where

increases are .5 K or less. On-shore winds are evident right along the coast line.

This trend continues over the next hour, where, by 16 UTC the east-west gradient

of potential temperature is between 1 - 1.5 K and on-shore winds of up to 4 m/s

are evident along the coast. Along the line indicated in Figure L.c, which extends

9

from 10 km east to 60 km west of CP4, the temperature difference is approxi-

mately 1.3 K. Over the course of the next two hours, the seabreeze convergenceline strengthens and begins to move inland. At 17 UTC the on-shore winds along

the coast have further strengthened and at 18 UTC winds are generally easterly

5-10 km inland. At that time, the temperature difference along the indicated line

is approximately 2.4 K. At 19 UTC the seabreeze convergence line is just to thewest of the CP3 radar, roughly 20 km west of the CP4 location. On-shore winds

are still strongest along the coast, where wind speeds are in the 5 - 7.5 m/s range.

Finally, at 20 UTC, easterly winds of up to 3 m/s can be found as far inland as 20

km and the temperature difference along the indicated line is increased to 2.7 Kat that time.

The CP3 and CP4 radars both performed survey scans at several low eleva-tion angles (0.50, 0.90, 1.50, 2.10, 2.70, 3.3°) between 14:21 UTC and 18:04 UTC.Examination of the data from these radars revealed that the CP3 data would not

be very useful for our purposes; since the view to the east was partiallyobstructed by trees and the seabreeze front did not penetrate very far inland

before 18 UTC, there was no seabreeze signature evident in the returns receivedby CP3. However, the CP4 radar, while it did not provide any information about

the flow over the water, did sample a significant portion of the developingseabreeze circulation both in the radial velocity fields and the derived TREC

wind vectors. Figure 2 shows the wind vectors derived by the TREC technique

from two successive scans centered at 1705 UTC (1659 - 1704 UTC, and 1706 -

1711 UTC), for the first four elevation angles. The data are shown on a radar-centered coordinate system with the x- and y-axis representing the eastward andnorthward distance from the CP4 radar. The geographic region and the windvector scale are the same as in Figure 1. As the elevation angle is increased,

boundary layer returns are restricted to smaller distances from the radar: at 2.1',the highest angle used for the TREC technique, returns are only available out toless than 20 km. The TREC motions at that time are generally weak (less than 2-3

m/s) and somewhat disorganized, displaying a fair amount of small-scale

variability.

10

4. Assimilation Exments

4.1. General remarks

The model integrations described below were performed on a horizontal and

vertical grid designed to facilitate ingest of CP4 radar data. The horizontal grid

was centered at the CP4 radar location and a uniform horizontal grid spacing of 5

km was used to match the output of the SPRINT program. The coast-line used in

the model is shown in Figure 3, which shows the fractional land area of each grid

point. Vertical grid spacing was variable, varying between 200 m near the

surface to 350 m at the top of the domain. Table 1 shows the location of the

staggered levels (used for vertical velocity) and tracer levels (used for all othervariables). A long time step of 10 sec and a small timestep of 5 sec was used.

(The model uses a time-split integration scheme, using a small timestep for terms

related to fast gravity wave motion.)

4.2. Control run

The forecast model was initialized at 14 UTC (10 EDT), using the 1404 UTC

sounding (see Figure 4) taken at TYCO airport, which is located approximatelyhalfway between the CP3 and CP2 radar sites. The sea surface temperature was

set at 301 K, based on climatological values. Figure 5, which is a horizontal cross

section at level 2 (the first model level above ground) at hour 2 of the forecast (16

UTC), shows a seabreeze circulation along the coast, with a temperature

difference in excess of 2 K across the coastline. The vertical cross section through

the CP4 radar location shown in the same figure shows the leading edge of the

seabreeze and the associated updraft centered at x=-10 km, i.e. 10 km west of

CP4, or roughly 16 km inland from the coastline. The temperature difference

between x=+10 km and x=-60 km (at y=0) is approximately 1.2 K. The updraft

has moved 20 km further inland by hour 4 of the forecast (18 UTC; see Figure 6),

and temperatures over land have risen by 2 K in response to solar heating,

resulting in a 3-4 K east-west temperature difference 2. This trend continues tohour 6 of the forecast (Figure 7), at which time the circulation has further

strengthened, temperatures inland have risen by another degree, and easterly

2Note that velocity vectors are plotted to reflect the exaggerated vertical scale of theFigures.

11

Table 1: Height of model levels in meters above ground.

Level Stagger level (w) Tracer Level (uv,O)

1 0 -1002 200 1003 400 3004 600 5005 800 7006 1000 9007 1200 11008 1400 13009 1600 1500

10 1800 1700

11 2000 140012 2200 210013 2400 230014 2600 249715 2850 271916 3150 299417 3500 332218 3850 367519 4200 402520 4550 437521 4900 472522 5250 5075

winds are evident throughout the domain with the seabreeze front updraftlocated at x=-60 km (at y=0 kin). Figure 8 shows horizontal cross sections at level4 (600 m) at hours 2,4, and 6 of the forecast. The evolution is quite similar to thatshown at level 2, but the temperature gradient is noticeably weaker. Verticalcross sections to the south of the radar (not shown) are very similar to the onesshown in Figures 6-8, except that the circulation is somewhat further to the east,in accordance with the shape of the coastline. Vertical cross sections to the northof CP4 (shown in Figure 9) show a somewhat disorganized secondary updraftpattern near x=0 at hour 2 of the forecast, which is a result of the complicated

12

coastline at that location. This feature is soon overwhelmed by the primarycirculation, however. In earlier model integrations using a larger time step, a

weak 2-Ax vertical velocity pattern developed at this location, leading to strong

numerical noise and an eventually unusable forecast.

Comparisons of the model output with the PAM data plots indicate that theseabreeze circulation is overpredicted by the model at the later stages of theforecast for this case. To facilitate comparison with PAM data, and the later

assimilation experiments, key features of the seabreeze simulation are

summarized in Table 2. For the PAM data, the location of the updraft maximum

was estimated from the convergence of the low-level wind field. It is evident

from the figures and Table 2 that at hour 2 (1600 UTC), the model simulation isstill in general agreement with the observations, both in terms of the temperature

gradient and the updraft location. At hour 4, the seabreeze front isapproximately 10-20 km too far inland and land temperatures are too high by1-2 K. By hour 6, the seabreeze front is almost 40 km too far inland and thetemperature contrast between the coast and inland is almost 2 K too large.

There are a number of possible reasons for these forecast errors. The availableatmospheric data indicate that there was no cloud cover or cold advectionobserved that day to account for the slower than predicted warming. Thus, the

most likely reasons are related to parameter choices for the surfacecharacteristics: the specified water temperature might be slightly too cool,

leading to an exaggerated land-sea temperature contrast; the soil type and/orinitial soil moisture might result in a soil that is too dry, leading to excessive

warming of the ground; or the albedo might be too small, leading to excessiveamounts of absorbed shortwave radiation. Since temperature errors are larger

over land than water, the land surface characteristics are probably the mostimportant factor. We did not attempt to tune the model any further for this

forecast. Instead, we used assimilation of TREC and SPRINT winds and thederived temperature fields, to try to improve the forecast.

4.3. WInd-only asamihlaton

This model run is identical to the control run, except that the model is nudgedtoward the observed (TREC and SPRINT) winds between hours 2 and 4 of theforecast (between 16 UTC and 18 UTC). For this assimilation run, the

13

Ta! .. 2: Comparison of key features of the sea breeze between the PAM

observations, the Control run, the Wind-only, and Full (wind andtemperature) assimilation runs. Locations refer to the x-coordinate at y=O,

and AT/ 70 km is the near-surface potential temperature difference

between x=+10 km and x=-60 km at y--O.

Feature Time PAM obs Control Wind-only Full

Updraft location 0 to -5 km -5 km -5 km -5 km

Center of 2 h 0 km 0 km 0 km

circulation 16 UTC

AT / 70km 1.2K 1.2K 1.2K 12K

Updraft location -10 km -25 km -20 km -10 km

Centerof 4h -15 km -10 km 0 km

circulation 18 UTCAT / 70 km 2.4 K 3 K 2.9 K 2.4 K

Updraft location -10 to -20 km -50 km -40 km -35 km

Centerof 6h -40 km -30 km -20 km

circulation 20 UTC

AT / 70 km 2.7 K 4.4 K 4.4K 3.7 K

temperature retrieval step is skipped in the assimilation procedure. Radar data

used for the assimilation consisted of full PPI scans at elevation angles 0.3, 0.90,1.5-, and 2.1- between 1604 UTC and 1804 UTC, which were available every 7minutes (aside from one 20 minute gap and three gaps of 10-13 minutes). Thus,

both SPRINT and TREC winds were available throughout the assimilation

period.

The objective analysis step of the radar-observed winds at the first model

level is shown in Figure 10, which shows the wind and potential temperature

fields before and after the objective analysis and the difference between the two

(the analysis increments). Wherever radar observations are present, they result

in a weakening of the easterly winds of the first guess, as is to be expected in

light of the forecast errors evident from the PAM data. The largest increments

are directly to the west of the CP4 radar, since the u-component of the wind is

14

sampled by both the SPRINT (radial) and TREC (total) winds. To the north andsouth of the radar, the radial components of the predicted and observed flow are

small, so here the westerly analysis increments are a direct consequence of theuse of TREC winds. Radar returns are absent over water, limiting the influence

of the observations to near the coast line. Since no temperature retrieval isperformed, there are no analysis increments of temperature. Analysis incrementsat level 4 (600 m, not shown) exhibit a generally similar pattern.

The effect of the assimilation on the forecast can be seen in Figure 11, which

shows the fields at the end of the assimilation period and the differences from thecontrol run. As is to be expected from the preceding discussion of the analysisincrements, the effect of the wind assimilation is the weakering of the easterlywinds near the radar site. Temperature changes are generally small. The largestchange is a warming of 0.3 K or less over the radar in response to the weakenedcold air advection. Wind and temperature differences at level 4 (not shown) arevery similar to those at level 2. The vertical cross section through the radarlocation at that time is shown in Figure 12. Compared to the control run, theseabreeze front is weakened and shifted eastward (by approximately 5 kin; see

also Table 2). By hour 6 of the forecast, which is two hours past the end of thewind assimilation, the beneficial impact of the radar data can now be seen to the

west of the radar location (Figure 13), a result of decreased westward advection

of easterly momentum. The vertical cross section (Figure 14) shows the center ofthe seabreeze circulation at x=30 kin, approximately 5 km east of the control runposition (see Table 2). However, the leading edge of the updraft is shifted east by15 km, resulting in a sharpened seabreeze front. As before, changes in thetemperature field are small and are a direct result of the changed advection andadiabatic cooling patterns.

Compared with the verifying PAM data, the wind assimilation results inminor improvements in the wind field and no improvements in the temperaturefield.

4.4. Wind and temperature assimilation

This run uses the full assimilation scheme between forecast hours 2 and 4 (16UTC to 18 UTC). TREC and SPRINT winds are used in the objective analysis andpotential temperatures are retrieved from the four-dimensional wind fields. The

15

first guess, analysis, and analysis increment fields at level 2, hour 3 shown inFigure 15 are quite similar to those of the wind-only assimilation run. Theanalysis increments at level 4, the first level for which a temperature is retrieved,is shown in Figure 16. It is obvious that the retrieval scheme is workingproperly. Temperature increments are negative inland and positive over waterand the immediate coast, thus reducing the water-land temperature contrast atthe 600 m level by up to 2 K (recall that the positive temperature bias cannot becorrected by the retrieval scheme).

The forecast fields at the end of the assimilation period show improved windand temperature fields at level 2 (Figure 17). Compared to PAM data, both thewind field and the temperature contrast (see also Table 2) is in much closeragreement. At level 4 (Figure 18), the effect on the temperature contrast is larger(a 1.4 K reduction), since at that level the model is directly nudged towardretrieved temperatures. The vertical cross section (Figure 19) shows thattemperature differences are largest at level 4 and quickly drop off below andabove. At lower levels, no temperature retrieval is performed (recall thatpressure retrievals are not performed at the lowest or highest level with winddata and that the temperature retrieval requires retrieved pressures atsurrounding layers). At upper levels, smaller impacts are related to two separatefactors. The first is the amount of data and resulting size of the analysisincrements. Even though wind data are assimilated up to 2 km, the datacoverage is restricted to a small area around the radar (viz. Figure 2). The secondis the smaller east-west temperature gradient in the control run. Forecast errorsat upper levels are smaller, with correspondingly smaller effects of dataassimilation. The updraft maximum of the seabreeze front in Figure 19 is atx=-10 km, some 15 km east of the control run position and close to that indicatedby the PAM data (see Table 2). At hour 6 of the forecast, forecast errors havegrown somewhat. Both the horizontal cross sections at levels 2 (Figure 20) andlevel 4 (Figure 21), and the vertical cross section through the radar location(Figure 22), show the updraft maximum to be at x=-35 km, almost 20 km too farinland compared to PAM observations (see Table 2). The difference pattern fromthe control run has been advected with the easterly flow since the end of theassimilation, as was the case with the wind-only assimilation run. Thetemperature difference fields show a slight weakening and broadening of thegradient between hours 4 and 6. Thus, the beneficial effect of the data

16

assimilation remains largely intact, indicating that the changes introduced by thenudging are not rejected by the model during the forecast. Even though forecast

errors grow after the end of the assimilation, they remain significantly smallerthan in either the control or wind-only assimilation runs. The beneficial effects of

the temperature retrieval and assimilation are illustrated by a comparison of thedifference plots in Figures 20b and 22b (showing differences between the full

assimilation and control) with those in Figure 23 (showing differences betweenthe full assimilation and the wind-only assimilation). The temperature difference

fields at level 2 are virtually identical, thus the entire improvement in thetemperature forecast is due to the temperature assimilation. Wind field

differences show a significant additional improvement in the full assimilation

over the wind-only assimilation.

5. Summary and concusiom

The real data tests of a single-Doppler radar data assimilation and forecastsystem have been conducted for a Florida sea breeze case over the Cape Kennedy

area (during the CaPE experiment). The model forecast in this case wasoverpredicting the strength and westward penetration of the Atlantic seabreeze.As was found in earlier experiments with simulated data, assimilation using

Newtonian nudging benefits from temperature data in addition to wind data.

The thermodynamic retrieval technique was successful in retrieving a horizontaltemperature gradient from the radar-derived wind fields that, when assimilated

into the model, led to a significantly improved forecast of the seabreeze strengthand position. Unlike the Observing System Simulation Experiments reported in

Hamill and Nehrkorn (1993), the real data forecast using winds and temperatureswas dearly better than either the control or wind-only assimilation forecast,while differences between the wind-only and control runs were comparatively

small.

The CaPE case was selected even though there was no convective

development along the seabreeze in the Cape Kennedy area that day, because the

seabreeze circulation was sampled well by the CP4 radar. Radar scan patterns on

other days during CaPE prevented tests of the technique for cases withconvective initiation along the seabreeze front.

17

The present study proves the soundness of the approach and feasibility of

single Doppler radar data assimilation. However, there are several factors which

limit the general applicability of the prototype technique in its present form to

thunderstorm forecasting. Because of the requirements for high vertical and

temporal resolution and good areal coverage of the radar data in the boundary

layer, this technique will only work if sufficient scatterers are present and if

appropriate radar scan patterns are used. A potentially more serious limitation is

that boundary layer convergence features (such as the seabreeze front) that can

be predicted by the simple prototype mesoscale model used in this study do not

account for all or even the majority of significant convective developments.

More typically, synoptic scale fronts, or mesoscale features of those fronts and

interactions of outflows from decaying cells with each other, or with other

convergence lines such as the seabreeze front, are responsible for convective

initiation. Modeling these complex scale interactions is a challenging problem

for which more sophisticated models are needed.

Cotton, W. R., R. McAnelly, C. Tremback and R. Walko, 1989: A dynamic model

for forecasting new cloud development. AFGL-TR-89-0011. Air Force

Geophysics Laboratory, Hanscom AFB, MA. 81 pp. [NTIS ADA2139391

Cressman, G., 1959: An operational objective analysis system. Mon. Wea. Rev.,

87,367-374.

Gal-Chen, T., 1986: Selected comments on the use of the divergence equation to

obtain temperature and geopotentials from an observed wind. J. Atmos.

Ocean. Technol., 3, 730-733.Gustafson, G. B., J.-L. Moncet, C. F. Ivaldi, H.-C. Huang and J. M. Sparrow, 1991:

Mesoscale prediction and satellite cloud analysis for advanced

meteorological processing systems. PL-TR-91-2008. Phillips Laboratorv,

Geophysics Directorate, Hanscom AFB, MA. 112 pp. [NTIS ADA 240510]

Hamill, T. M., 1992: Prediction of thunderstorm initiation through 4-dimensional

data assimilation of doppler radar data. PL-TR-92-2029. Phillips

Laboratory, Directorate of Geophysics, Hanscom AFB, MA. 86 pp,

ADA251243.

18

Hamill, T. M. and T. Nehrkom, 1993: Sensitivity Testing of a single-Doppler

temperature retrieval and forecast system. PL-TR-93-2071. Phillips Lab.,

Directorate of Geophysics, Hanscom AFB, MA. 86 pp, ADA267278.

Kropfli, R. A., 1986: Single Doppler radar measurements of turbulence profiles in

the convective boundary layer. 1. Atmos. Ocean. Tehnol., 3, 305-314.

Liou, Y.-C., 1989: Retrieval of Three-Dimensional Wind and Temperature Fields

from one Component Wind Data by using the Four-Dimensional Data

Assimilation Technique. M.S. Thesis, University of Oklahoma, Norman,

OK, 112 pp.

Mohr, C. G., L. J. Miller, R. L. Vaughan and H. W. Frank, 1986: The merger of

mesoscale data sets into a common cartesian format for efficient systematic

analyses. J. Atmos. Ocean. Technol., 3, 143-161.

Pielke, R. A., 1984: Mesoscale meteorological modeling. Academic Press,

Orlando, FL. 612 pp.

Stauffer, D. R. and N. L. Seaman, 1990: Use of four-dimensional data

assimilation in a limited-area mesoscale model. Part I: Experiments with

synoptic-scale data. Mon. Wea. Rev., 118, 1250-1277.

Tripoli, G. J. and W. R. Cotton, 1982: The Colorado State University Three-

Dimensional Cloud / Mesoscale Model - 1982; Part I: General Theoretical

Framework and Sensitivity Experiments. J. Rech. Atmos., 16,185-219.

Tuttle, J. and G. B. Foote, 1990: Determination of the boundary layer airflow

from a single Doppler radar. J. Atmos. Ocean. Tech., 7,218-232.

Vemuri, V. and W. J. Karplus, 1981: Digital Computer Treatment of Partial

Differential Equations. Prentice Hall, Inc., Englewood Cliffs, NJ. 449 pp.

Williams, S. F., K. Caesar and K. Southwick, 1992: The convection and

precipitation electrification (CaPE) operations summary and data inventory.

National Center for Atmospheric Research, Office of Field Project Support,

Boulder, CO. 425 pp.

Wilson, J. W. and W. E. Schreiber, 1986: Initiation of convective storms at radar-

observed convergence lines. Mon. Wea. Rev., 114, 2516-2536.

19

PAM data for 9107/23 14:00:00: Pot T (DG K)

i+ 300.2,

299.0300.

3005o300. 5, 15:0 0

S ,-O, 30 3.00-k

30030.

P..0

aS moo.- _..._&

3W. O0.4 30.S 300.

*1 *300t 300.7_

299.9

5 Wsu scale:

PAM daua for 91/07/23 15.00:00- Pot T (DG K)

71301.1.

301.23013012

302%M73014 0.k

301.7,P

305 M728 31.7

43018W7*30

310 3021 6301* 303D! A 3O.t.0 301.0

SD0.0, 301.5_-

30091

5 W~S mCii:

Figure 1: Plots of PAM surf ace da.ta. Station locations correspond to the origin of thewind vectors; potential temperature is plotted above and to the left of the stationlocation. Position of radars is indicated by asterisks.

20

PAM data for 91/07/23 16:00:00: Pot T (DG K)

301.9

302.o0•2

3W030.0 302.

3027 .. 302.t

,1 3 0 3 .1 02..9

303.0

302.2

303.1303.0 33022 301.1

30 1.9L

s n/s scoe":

PAM data for 91/07/23 17"00.00: Pot T (DG K)

302.3,

302.S3023032.6 W

d W1 3 9S = %.7,

025 27203.2 3•140w", 303.9

303.6,303.03024 301..O !

3*02.3, 302.,

30&33

5 W•s scmas:

Figure 1 (continued).

21

PAM data for 91/07/23 18:00:00: Pot T (DG K)-IO 41.15 .J.5 70

L~~t 302.4, 04

303.3304.

r ! 303"'&3.- 343.,

30 303.13MN% 30&4.

r.31

1 303O

5 n•a scabe: _

PAM data for 91107/231 9:00:.00: Pot T (06 K)

304.4

MR -%n 303.4

" 0.304.8a 303.2.3

304.9.

S304-0. 34-_ 302

r.11

5$ns esoa:

Figure 1 (continued).

22

PAM data for 91/07/23 20:00:00: Pot T (G(3 K)4 IID -41.15 4IL 7-5V

L71 30.

306.2,

304.4 •O04q 3t

5 •s' sco: sca:

Figure 1 (continued).

23

TREC VEL VECTORS IWITH QCi165916 TO 170603 EL- 0.3 910723

CORAIN.CORMAX.TNRVAR.THRVOF.SRAO.ARSIZ= 0.40 1.50 25.0 1.0 4.0 7.0

49 NN .

86..

-2.-0.•

210. .' . . . . . . . .. . . . .

U..

a -2in.'.. :

-4in. . -:;;

-BI. -60. -41. -20. I. 20. 40. 6O. so.

TREC VEL VECTORS (WITH QC)165940 TO 170627 EL- 0.9 910723

CORCIN.COR1AX.THRVAR.THRV0F.SRAO.ARSIZ. 0.40 1.50 25.0 1.0 4.0 7.0

60.

40.

28.

-26.-go L0 . . ... . ..

-86. -60. -40. -20. 6. 20. 46. 66. so.

• .. .o.

Figure 2: TREC derived winds valid for 1705 LITC, over the same geographic region andwith the same wind vector scale as in Figure 1, for elevation angles 0.30, 0.9, 0.¶and 2.1". (CP4)

24

TREC VEL VECTOiRS (WITH QCI

170005 TO 170651 EL 1 5 q10723

CORtIN.CORAAX.THRVAR.IHRVOF.SRAO.ARSIZý 0.40 1.50 25.0 1.0 4.0 7.0

66

44.

24.

-460.

-60.

-66. -60. -46. -26. 0. 20. 46. 60. so.

5J. .1.

TREC VEL VECTORS (VITH OCT

170029 TO 170715 EL, 2.1 910723COW IN. CMMX, TNRVAR. TNRVDF, SRAD, RS)Z- 0.40 1SO 25.0 1.0 4.0 7.0

be4.

40.

-g. -60 -411 -28. 6. 20. 49. 60 S.

5). 5,.

Figure 2 (continued).

25

land/water fraction80

1.0

0.9 60

0.8

0.7

0.6

0.5

0.4-20

0.3

0.1

0.0

-80-80 -60 -40 -20 0 20 40 60 80

Figure 3: Fractional area of PL-3D gridpoints covered by water. Model domain showncorresponds to the area plotted in Figure 1.

26

5000

4M0

a 3M0

2M0

1000

0 . . . . . . . . . .295 300 305 310 315 320 325

Thea (K)

5000

4M0

4 1. .. .. ..... ... .. .

b 3000:: ° ...

2000 -" .

010

-6 -4 -2 0 2Uwind Vwind (mas)

Figure 4: The sounding used to initialize the model runs: potential temperature - top

panel; u (solid) and v (dotted) - bottom panel.

27

TINE: 7200.0S / 2.00H SLAB: K- 2

60.0- ''

40.0-- .. .. . .. . . .. . . . . .A

. . . .. . .d A .

20.0- . . . . . . . . .~~~. . . . . . . . . . .

.. .. .... .. .....0" -- F

. . . . . . . . . . .. . . . .

-20.0 .. " ".o ... . . . . . . . . . ..... .

S. . . . . . .. . . . . ..S-20 0 . . . .. . . . . . . .....

-6 '0° .0. ... . ..S.. . . . 4.. . . . .. .. .. .C,

-80.0 . .... .

-80.0-60.0-40.0-20.0 0.0 20.0 40.0 60.0 80.0

X(KM)

PROM 290. TO 330. BY 1, LABELS - I

TINE: 7200.OS / 2.00H SLAB: Ju 17

5000:*,-:

319. " 319.

4000.. . . .. .,. . 317... . .... . . . .. . . . 347 . . . . . . . . ..7.

3000.----- - - - "--- 3"--- -- -------------- 313.. ..... ...........300 . .. . .313 . " . . . . ' _ .3L . .. . . . . . . . ...

b 31..... . . . . 3............311.. . ..........

Z--------0. 309 ....

~2000.-- - - - - -------.--------------------- --- - - - - - - - - - ..... - -

. .. ........... .- - - - --......

0 . . . . . .. . . . .. . . . . . . . . . . . . - -• - - - - -

.. . . . . . . . . . . . .. .I . 11 J "o .:

-80.0 -60.0 -40.0 -20.0 0.0 20.0 40.0 60.0x (EM)

FROM 290. TO 330. BY 1. LABELS * !

Figure 5: Horizontal cross section of winds and 0 at level 2, and vertical cross section at

y=O,for hour 2 (16 UTC) of the control run. Dotted line in horizontal cross section

denotes the coastline. The vector scale is given in m/s.

28

TIME: 14400.OS /4.OOH SLAB: K= 2

80.0.-

4- 0 . .. % %. s

60. Oy -I *=l ** S..,;

* 2~~~0.0 4-- ' SS

-0. 0, le'-- - - %.~ a.*SSS~

-60.0- I I I. .I It*IIIS

- - lees:

a 0 0 a - -.

-90.0-60.0-40.0-20.0 0.0 20.0 40.0 60-t, 80.0

UITI Voom

FROM 290. TO 330. BY 1. LABELS *I e~e

TINE: 14400.OS I4.0011 SLAB: Jm 17

52000.,-:D

-80.0 -- -60 -4. -2. 0. 20. 40. 60.0 ---- ----319. (319.

4000.--~~~ ~ ~ ~ ~ ~ *5! .17...... 37.....

FRO 29. TO 330. BY 1.LAEL

Figue 6: Hoiona crs seto of wid and -at lee 2, an vetia crs section-at2000, hou 4 (1 .of th coto run Dote lin in hoiona crs section

dente th3oslie h vco7clei ienins

29-

TIME:. 21600.0S I 6.OOH SLAB: K= 2

60. -004002. .02. 00 008.

20.M 29.T"30N'I IDL

500.

319. 319

400...........317....................31~..........

-80.0 -00 -00 -00 00 20 400 6.

X (KM)

MIT .a.-

FRMN 290. TO 330. BY 1. LABELS j

Figure ~ IME 7:00O Hoiona cross sectio of wid1n7 tlveadvrialcosscina

y 000 for2 hou 6 (232)o1h.onrlrn otd iei oiota rs etodente th coslie Th veto scl is gie in -in/s.---- -----

319. 339

TIME: 7200.0S / 2.00H SLAB: K= 4

80 .0 - 1. 1 1 1 1 1 1 - I I I I . , , , .r ,

80.0-"".. . . . . . . . . .. . S S iill liii 'dlii 1.1

60.0- * .'5 5 55 5 i i i

2 .0 - . . . . . . . . .. . .'. .

0 .0 . . . . . . . . . . ....'. . ,

40.0 . .... . . ... . .iii-,. .. .. . . I; A!•" . liii, '

S.. .. . . . ' " :. " £5 ,..I I I I

-20.0 ... . . .

FROM 290 TO 33 SY I LABELSI

TIMEI I S I 4

- 0.01 f . ..:

Yy:

S-20.0 . ............. .. " , , ,

0 . . s a , , T .| I. 4

UIeZ

2 0. 907 TO e e AES

TIE:140.0 I4.0 SLAB: K= 4Ss:

P4,,-80.0

- -... 60....• 0. -e ,::,e,

-80.0-60.0-40.0-20.0 0.0 20.0 40.0 60.0 80.0X(10E)

MIT VOCMFROM 290 TO 330 BY 1 LABELS I

8-0.0 ./ ...

- " -.- ---- -- ..- I g/// ' / *1/ 1 4 /.

/, " 1. .."I / .1 1. /. . 1 /I I I /

-40.0 -). . - : i ' / / / - / /IIIII '

,". ~ I ', / /" , ,, / / i I /

-80.0

-80.0-60.0-40.0-20.0 0.0 20.0 40.0 60.0 80.0

FROM 290. TO 330 BY I. LABELS * 1 o...0 •o

Figure 8: Horizontal cross sections of winds and Oat level 4for hours 2, 4, and 6 (16, 18,and 20 UTC) of the control run. Dotted line denotes the coastline. The vector scale

is given in m/s.

31

TIME: 21600.0S / 6.OOH SLAB: K= 4

60.- .---- .--.

20. !•,'i,"~- -..-" -" -" -.. .

. - . .-.- ..-- - .- - - - - -40. - --

--0. d0 0 0

rRo. 29.o TO 330. BY, 1.,UM.,

Figure 8 (continued).

32

M.: . _- I II II --- -

TIME: 7200.0S / 2.0OH SLAB: J= 23

5000.* ....

319. 319.

4000. 317. 317..

.. -.-.-.- 3"15" ..------- - " . .-. --------- --3-.

3000.---- ---------. 3J3 ------ - - _----- --- - -3 .. . . . . . . . ..------------

"--------- -- - - - - -..............1-3.2000.- -.. _ ....-.-.-.-.-.. 311. . ....

0 . ...... . .-.. ... ... . . .

-000.0 .0 .0. 2. 0.0 . .0.60.0

101C 104)

FRM90 T 306. BY,0ABLS-

3 ......------------ --- 3-...-,000' -- -- ,- -- -............

1 ~-4 - I--

-~~ .. .~ . . .\ ' .- . .

0.1

-80.0 -60.0 -40.0 -20.0 0.0 20.0 40.0 60.0X (KM)

UNIT VOCI

FROM 290. TO 330. BY 1. LABELS I

TIME: 14400.0S / 4.00H SLAB: J= 23

5000. *........ -'1

319. 319.

4 0 0 0 .- . . .. . . 3.17 . . . . . . . . . . . . 317 . . . . . . . . . . .

- -. . . . -. . 3'1 5 7-- - - 3f5.- _ - -- - - - - - - -

3000. -- _ 3-3 . . . . . . . . . . . .- - 313 - - - - - -

-. . . .- - - - - - - . . . .- . . . . . . . . .-

j2000 . . .. -- m o3 e -,--- -.. . . . . . . . . . . . . . . . . . .

co t o u . . . . . . . . .3 '. . . . . .

33

-80.0 -60.0 -40.0 -20.0 0.0 20.0 40.0 60.0X (KM)

FROM 2-90. TO 330. BY 1. LABELS I

Figure 9: Vertical cross section of winds and Oat y=+25 km, for hours 2, 4, and 6 of the

control run.

33

TIME: 21600.0S / 6.00H SLAB: Ju 23

-319. 3319.m~~~~~ . .. ... . . . . . . .. . . . . . . . ..

4000.-" . . 317 . . . . . . . . . . . . 117 . . . . . . . . .

-00.0 - 410. -2 0 .31,5 ......- - -. . .. - .- 3- -- '-= - -- 1

32000 .-- .- - -" '• "" - - - - - . . . . . . . ..a13 - - - -

2 R O M 2 9 0. T O 3 3 0. .B.Y. .1... .L.AS.. . . '0) - -: -: -3 7 -. . .

1000. -• -

0 34

-80.0 -60.0 -40.0 -20.0 0.0 20.0 40.0 60.0x (KK)

Uml vmCml•

FROM 290. TO 330. BY 1. LABELS * I

Figure 9 (continued).

34

TIME: 10800.0S / 3.00H SLAB: K= 2

80.0 ....'. .. . . , , . ,

60.0 .. . . . .

S'-0 -, . . . . . I

-40 .0. . .. . . . . .....40.0 ... . . . ..

II6 II / j61I- *. +."66 11 1

-80.0 "

-8 . -6 . -4 . -2.0 0. 200 4 0 6 .0 8 0

TIME : S . . . .

20.0 ..... .......... . . .... .

-40.0. ..........

460.0..........

% %

S.-,. . . .. . . . ...

-2.0 . .~ ~ .. ..

-4 . - . . . . . . .. . .- . •# •

S- 20 .0 .... . ... .:I>. I-, I I - - - . . . . . . .

.4 ° ... .. .... ...

. .

-80 .0-80.0-60.0-40.0-20.0 0.0 20.0 40.0 60.0 80.0

x(KM)

UNIT VICIOS

FROM 290 TO 330 BY I. LABELS I 1

TIME: i0800.0S I 3.00H SLAB: K 2

wind-on0'ly assiilaion fis guss anlss an anlyi inrmns Dote ,ln,

4o~o -, ,, ,, ,, ... 66*5,6,,, ,800. .

"sow as the symb l "R

""351 1

j.20.0............- . .. g1 6 1 4

0.0.. . .. . . .. *.

b -20v.0................. .........- :

-40.0...,............ _......--- : .

"-60.0......................... I

-...u"..,................-.. :-80.•0 • s . • . . .. .. .. .• "

-80.0-60.0-40.0-20.0 0.0 20.0 40.0 60.0 80.0

FROM 290 TO 330 BY I LABELS * -4~_.•o

Figure 10: Horizontal cross section of winds and e at level 2for hour 3 (17 UTC) of thewind-only assimilation:first guess, analys is, and analysis increments. Dotted linedenotes the coastline. The vector scale is given in rn/s. The CP4 radar location is

shown as the symbol "R ".

35

TIME: 10800.OS / 3.00H SLAB: K= 2

80.0 -. .

S.. . . ... ..:.. .'.. .. . . . . . . . . . . . . . .. . .

60.0" . S.. .. . . . . . • ,- :. " . . . . . . . . . . . . ..

S.. .. . . . . -- '• , > ;. . . . . . . . . . . i

40.0 -

. . . . . .*:~ .-

20.0 .. . .. . -......... .......- ... • . . . . .

.. .. .. . . . . . . - _- - . . . . . .. . . ..

.0 . . .... . . . . ... .-. ,. .,. ... .. . . . . .

........ -.. .. .

.. . .... O " . ... . .. ,.. .. . . .. ..

. ... . . .. . . . . , . .. . . ...c ~~~-40.0...............- - iii!!

-60 . . . . . . . . . . . ... .. . . . ....

S. . . . . . . . . .. . . ./ P ' .. ". . . . . . . . .

-80.0-80.0-60.0-40.0-20.0 0.0 20.0 40.0 60.0 80.0

X (KX)

Figure 10 (continued).

36

TIME: 14400.05 4.OOH SLAB: K= 2

60... -p %

-0.0.06.-002. . 004. 008.% %D

20.M 29.T030 YI LBL

_80.0:p

-8 .-0.-0.-00 0. 00 4 . 008 .

TIME: -14 i+9.OS 4. OO SLA: =S-. - 0.0 - ' - -I-. .. s.'.s.

-60.0-Jfl.f

-80.0-

-8.0.60040-2. 0. 20. 40. 60. 80.0

0. 0- .......

%U! %~20.0 -- %% %

>RO .l TO . BY% ABL

Fiue 1 Hrzntlcrs ecin fwid ndOorlvl40t.or0-1 UC: id

only -0. asiiain an d. e. e fro cotrl Dote lin deoe th coatlne

The46 veto scl is gie in rn/s... ...

800-0.-0.-2 . 00 00 0. 0378 .

TIME: 14400.OS / 4.OOH SLAB: J= 17

5000.7

319. 319.

4000 . .. 17. . .. . . . .. . 317 , . .

- 3 .. . . . .I . . . . . . . . . . . 3- . . . . . . . . . . .

3000. --. . 33, -..- 7--- Z3)-3 - --------------... .

7-. o .. . . . ..-. _- 311,•2o. • 3•---- - -, - -i~. . ..309;• - "- "- -" -" -" - --

1000 ...... • \ \ \ '. " /I/ " . . . . .

* .. . . . .. . I -, uV• -

-- -- - - -3'%'3

i- i --- . - - - - - -

-80.0 -60.0 -40.0 -20.0 0.0 20.0 40.0 60.0X(KM)

FROM 290. TO 330. BY 1. LABELS * 1

TIME: 14400.08 / 4.00H SLAB: J= 17, , f l t f ! I I .. .

5000.--, , , I It I | ! I ti ..... ....... '.. . . . .

3000..- . .• • t . ., , . . .......S. . .. ,,x \ •',_• • . ,,,_, , .........................

S. 'I " - , , i ........................S,• . ...- . ......

•2000.- ..... . '. . , ,..

-q ." " (4 • -"% , , , L(, 185)..............

1000.

, o _ . . - - -...

-80.0 -60.0 -40.0 -20.0 0.0 20.0 40.0 60.0

X(KM)MIST WOCTO

FROM -1. TO 1. BY .2 LABELS * I

Figure 12: Vertical cross section of winds and Oat y=O for hour 4 (18 UTC): wind-only

assimilation; and differences from control.

38

TIME: 21600.OS /6.OOH SLAB: K= 2

20.

-.80.06.-00200002. 4. 008.

860.0- -. 31

60.0 29. TO-330. B ... LABE .. ....

. ................

. . .

40. 0

20.0. .--. . . . . ... .'

20.0 -

b - 0.0 .:.. .1 . . . .. ....

-40.0---

600- ,,/,l

-80.0 I I-80.0-60.0-40.0-20.0 0.0 20.0 40.0 60.0 80.0

X(KM)

PROM -] TO I BY.2 LABELS * I 1 l

Figure 13: Horizontal cross section of winds and 0 at level 2for hour 6 (20 UTC): wind-only assimilation; and differences firom control. Dotted line denotes the coastline.

The vector scale is given in rn/s.

39

TIME: 21600.05 / 6.OOH SLAB: J= 17

5000.

319.

00

FRO 290. TO 330 BY .. LAEL s .

5000.:-

-0 .

40 0.1 1 . .(-..2.6.

-80. -6 . -4 .0 -00 00 2 . 4 .0 6 0

FRO 29. TO30 Y1.LBLS

3000. .-- *

40 0 - .I. .. . . . . .H01 9

.. ~ ..................

300:. .L..~ . ...+ i I. .... ....I . I . . : :H .-I )

-800.0_.. -6. -4. -2. 0. 20. 4 .0 6.0..

FROM -. TO 1. BY .2 LAEL .

040

TIME: 10800.OS / 3.00H SLAB: K= 2,

80 .0 .. .

60 .0. ........ .... ..

""60 0,- 1 " .. .I I I . I I

40.0 -. .

" It• / ' * • '-20.0

- . .

0 00

S-20.0--, .......4• • • o

". . . . . . . . . . . .. . ........ .- '" . . . ,

-40.0"-, ,, .... .....a-40.0..................-•..-,.- .... ,

-80.0 '

-80.0-60.0-40.0-20.0 0.0 20.0 40.0 60.0 80.0X(KK)

FROM 290. TO 330. BY 1. LABELS * I

TIME: 10800.OS I 3.OOH SLAB: K= 3

80.0 .,.--- -• ..•_.. . • .. . .. ..me-. . . . . . . . ..# e

60.0,- ... h....

'II II% .. . . .1 I It I I . I

20.0 -,,,,,,S St- " ....0............ . .. . I I .

-o.. . . . . . . ....... - . -•• - . #2 -. .. . .I I I

-60.0. ..............

S- S

-20.0 - . . ... I. .

-- .%S ,

-40.0', •

-60.0,-, I. .. :'.

-80.0-80.0-60.0-40.0-20.0 0.0 20.0 40.0 60.0 80.0

X(KM)

FROM 290. TO 330. BY I LABELS " I

Figure 15: Horizontal cross section of winds and 0 at level 2for hour 3 (17 UTC) of the

full assimilation: first guess, analysis, and analysis increments. Dotted line

denotes the coastline. The vector scale is given in mis. The CP4 radar location is

shown as the symbol "R".

41

TINE: 10800.OS / 3.OOH SLAB: K= 2

80.0-

40.0- .. ...

0.0 - " 'R

-40.0--

260.0--

. . . . .

-80.0-60.0-40.0-20.0 0.0 20.0 40.0 60.0 80.0

Figure 15 (continued).

fIME: 10800.0S /3.OOH SLAB: K= .

80.0~

40.0 . . ..

-60.0

-0.0.

.2.-8 0-0040- 2 0 0. 20 ..0 4.0 6.0 80.0.

..~~~ ~ ~ (101)... .. .. .... ~~~~~R . ... .

PRO. .. O .. Y 2 .AEL .

Figure~~~~~~~ ~~~~~ 16 Hoiona cr. set. of wid an .at lee 4frhu. 1 T)ohfull ~. asiiain anl.i increments .. Dote lin d.oe th coslie The .I...

vetrscl s ie i ns.TeCP aa lctoni hona tesmbl0"

-8.0600400-0. .0200 00 4.28.

TIME: 14400.OS / 4.OOH SLAB: K= 2

S0. --- ----

4 0 057 . .. . .

20. 0- p

20.0 .. .. ....2- 0.. %%* i i

..0.0 .-. .-. . .... . .. '.

-60.0-,

-80.0--

-80.0-60.0-40.0-20.0 0.0 20.0 40.0 60.0 80.0

FROM 290, TO 330. BY 1. LABELS I ~sssss•o

TIME: 14400.0S I4.00H SLAB: K= 2

800 .%* i

60.0--. . . ." . . . . . . . "

- ------- "

-40.0 --- - - -. -'SSSS

20.0--... ..

0.0 -------

----20.0 --......... ---- ... .. . .

-40.0-: 5.. . . ."

-80.0-

-80.0-60.0-40 0-20.0 0.0 20.0 40.0 60.0 80.0X(KM)

UNIT VNCI

FROM -2. TO I. BY .2 LABELS " I

Figure 17. Horizontal cross section of winds and S at level 2for hour 4 (18 UT2: full

assimilation; and difterences from control. Dotted line denotes the coastline. The

vector scale is given in m/s.

43

800I ----

60.

- - .. S., I-I I-I

TIME: 21600.05 6.OOH SLAB: K= 2

60.

-8.-004002.0.02..00 008.

-82 -00-002.0 0.o00 006008.

X (KK)

FROM -9. TO 330 BY 1. LABELS I

Figure ~ TME 18:0.O Horionta cross seto f id n a ee 4fo or4(8UC:flassimiation and dif ne fro coto.Dte .iedntstecatie h

veto sal i6gve.i0- /s

40.0-44

T'fZ: 14400.OS / 4.00H SLAB: Ju 17

5000." .....

319. 319.

4 0 0 0 . . . , . . . U 7 . . , ... . . 3,7 .. . . . . . ..

30 0 - . . .:• . "'. . . . . . . •. .. . . . . . . ..- - - - -

3• 000.'- _ U,-3 -" - - - - -3• -. . . . . . . . ..- - - - -

--- - - - - - - -

3000.-- - - - - - 13 lo ..

a- ---------- --------*........................ ........... 31............. '""" . 1. . ........

...................................................b"• . ;, .... t ........

1000.---------: -- s'............o . .. . . .... .. . . .

S- - ---- - -- -- - - --0.A-80.0 -60.0 -40.0 -20.0 0.0 20.0 40.0 60.0

X (KH)

FROM 290. TO 330. BY 1. LABELS 1 I

TIME: 14400.OS / 4.00H SLAB: J= 17

5000.- ~~~~~ ..., , , , , ., .... ......4000. ,. a ~ a ~ i ., ..

,0 ... a .. .....

. , , • i 1 1 I I i , i. . ., .• . . . . . . .

42000.-

a.FOM -.. TO. . BY .2 LABEL, . 1,., I * . . . .

13000.- • • . . .

as iao -0si•milation; ad2 -0-.0o co nr o.... 0

FROM - 1. TO 1.BY.2 LABELS.45 IFiur 19 Vetia cros seto of wid an Oat r=o hou 4 (18 UQ M

assimilation; and differences from control.

45

TIME: 21600.OS /6.OOH SLAB: K- 2

-4 .- 004000...02. 00 008.

80.0

-40 00\ \\\ ~ %~

-60.0 '

-80.

-80.0-60.0-40.0-20.0 0.0 20.0 40.0 60.0 80.0

FROM -t. TO 330 BY 1. LABELS *I0

FigureTIM 20:0O Horionta cross setoKf=id n a ee 2orhu6(2LIC:fi

6046

TIME: 21600.05 6.0014 SLAB: K= 4

80.0

- - - - - - - -

L,------- - -~ -

20. ., .-Eg.E .-V . .-

... .$5 .... ..

0 . - . - -. ' ' r "-" "

-80.0-60.0-40.0-20.0 0.0 20.0 40.0 60.0 80.0

UNIT VEL'M

FROM 290. TO 330. BY 1. LABELS I

TIME: 21600.0S /6.0014 SLAB: K= 4

80.0 tt f~44I I,

60.0

40.0-'" -- - -. r

Al

20.0-~

-800.06.-002. . 004. 008.

FROM -I ~TO IBY .2 LABELS *1

Figure 21: Horizontal cross section of woinds and 0 at level 4for hour 6 (20 UTC): full!assimilation; and differences from con trol. Dotted line denotes the coastline. Thevector scale is given in rn/s.

47

TIME: 21600.OS / 6.0014 SLAB: J= 17

4000.- -317. . . . . ... . 317 . . . . . .

a

-80.0 -60.0 -40.0 -20.0 0.0 20.0 40.0 60.0

X (KMN)

FROM 290. TO 330. BY 1. LABELS * 1

TINE: 21600.05 6.OOH SLAB: J= 17

5000.-

1000.

-80.0 -60.0 -40.0 -20.0 0.0 20.0 40.0 60.0X (1M)

FROM - 1. TO 1. BY .2 LABELS * I 0.00.0

Figure 22: Vertical cross section of winds and Oat y=0 for h-u 6 (20 UTC): fullassimilation; and differences firom control.

48

TIME: 21600.OS / 6.00H SLAB: K= 2

80.0.

60.0- '\\\\ \\\\\\\ss\,, ,

40 .0- -,.

20.0"- 4

---3- - - - - -- - - -

-20. 0- S -" -

-40.0- , " .- .

-80.0 _ ."'-

-80.0-60.0-40.0-20.0 0.0 20.0 40.0 60.0 80.0X(KM)

FROM -1. TO I BY •2 LABELS * _

TIME: 21600.0S I 6.OOH SLAB: J= 17

5000..1

. • •~ . . . .| . . . ... . . . . . . . . . . .. .4000 . - .. . . . . . . . . . . . . ..

. .• 2..' . . . ... .

1000.1 0 ".A . .•'- . . . . . .---.

-80.0 -60.0 -40.0 -20.0 0.0 20.0 40.6' 60.0X(KM)

FROM -I. TO 1. BY .2 LABELS * I

Figure 23: Horizontal cross section at level 2, and vertical cross section at y=O, of windsand 6 for hour 6 (20 UTC): differences between full assimilation and wind-onlyassimilation. Dotted line in horizontal cross section denotes the coastline. Thevector scale is given in in/s.

49