High Latitude Precipitation: AMSR, Cloudsat, AIRS

Bob Adler (U. of Maryland/NASA Goddard)

Eric Nelkin (SSAI/NASA Goddard)

Dave Bolvin (SSAI/NASA Goddard)

George Huffman (SSAI/NASA Goddard)

and GPCP, too

MotivationTRMM Multi-satellite Precipitation Analysis (TMPA) limited to 50°N-50°S--desire high

time resolution global analyses approaching and through the GPM era

TMPA

• Take advantage of current and future developments by others in precipitation estimation applicable at high latitudes (e.g., high frequency microwave [150-200 GHz]--Ferraro, Jackson, Staelin, etc.)

• Develop empirical technique using AIRS (and/or other sounders) as “fall-back” when/where more physically-based microwave algorithms fail--especially over land

• Develop merging procedures to produce globally complete, ~3-hr analysis

Approach

January example 3B40RT, part of the TMPA

Current AMSR, SSM/I, AMSU estimates leave large gaps at high latitudes (and not so high latitudes) over land

QuickTime™ and aVideo decompressor

are needed to see this picture.

Daily GPCP Product (1997-present)--Huffman et al. (2001)

Uses SSM/I to Set Rain Frequency Statistically, but Daily Variations Determined by IR

High latitude based on TOVS/AIRS adjusted to match GPCP monthly which includes gauges corrected for wind loss

Current Monthly and Daily Globally Complete Products--GPCP

• For daily precipitation TMPA now a better choice at lower latitudes

• Daily averaging hides many problems that become obvious when doing instantaneous to 3-hr estimates

THE TOVS/AIRS (IR/MW) ALGORITHM

• Susskind et al. (1997) developed a calibrated cloud volume proxy from TOVS

Precip = revised cloud depth * cloud fraction * ƒ ( latitude, season )

• The calibration is TOVS swath data vs. daily station precip data

• Results show low precip rates, very high fractional occurrence• done as a regression• uses instantaneous data as a proxy for daily data• has only one sample for the day

cloud top ht. – ( scaled RH + scaled cloud fraction )

0 = sat. sfc500 mb9 = dry “

0 = overcast4.5 = clear

• In current GPCP products TOVS/AIRS-based estimates are adjusted area-wise by comparison with SSM/I (GPROF) at lower latitudes where confident and extrapolated to higher latitudes, adjusting pdf of precipitation rate and constraining total by monthly GPCP (with gauges over land)

Comparison of GPCP Daily (1° lat./long.) and Finland (FMI) Gauges for August 2005 and February 2006

As Starting Point for Evaluation of High Latitude Satellite Precipitation Estimates Now and For GPM

GPCP daily product is research product using various satellite data sets as input and monthly GPCP product (which contains monthly gauges with wind loss) applied to restrain bias.

At latitude of Finland satellite information is from TOVS/AIRS.

Daily analysis is globally complete and extends from 1997 through 2007 (updated about 2 months after real-time).

Reference: Huffman et al., 2001: Global Precipitation at One-Degree Daily Resolution from Multi-Satellite Observations. J. Hydrometeor.

Comparison of GPCP Daily, 2° Long./1°Lat. (~100 km) August 2005

Scatterplot of all 8 Daily 2°x1° Precipitation Values for the month within the 4°x4° Green Box (previous slide)

Time Series of Daily Precipitation for the 2°x1° Red Box

% Bias Diff = -14%Corr = 0.6

% Bias Diff = 7%Corr = 0.72

Summer results “good”, but with significant room for improvement

Comparison of GPCP Daily, 2° Long./1°Lat. (~100 km)February 2006

Scatterplot of all 8 Daily 2°x1° Precipitation Values for the month within the 4°x4° Green Box

Time Series of Daily Precipitation for the 2°x1° Red Box

% Bias Diff = 47%Corr = 0.52

% Bias = 60%Corr = 0.30

Winter results worse, with wind loss major factor in bias

Additional analysis continuing

Also looking at Canadian data set and BALTEX data

(Image from http://cloudsat.atmos.colostate.edu) Both AIRS and AMSR-E are aboard Aqua.

COMPARISONS WITH CLOUDSAT

Launched in 2006, CloudSat, with its Profiling Radar, flies in formation

with the other satellites in the A-Train constellation.

CloudSat views on a nadir track, providing a “curtain” of cloud/precip data at all latitudes.

High-latitude Southern Hemispherewinter case, with precipitationnear the center of the swath

9-10 July 2006, 22:30-01:30 UTC

Original AIRS precipitation is toowidespread in both high latitudesand the tropics.

Calibrating to AMSR-E greatlyreduces spatial coverage; ratesare boosted closer to AMSR-E.

Mapping via histogram-matchingcan be extreme, due to limitedrange of AIRS rain rates(max. ~1.2 mm/hr).

AMSR-ECalibrated

AIRSOriginalAIRS

CALIBRATION WITH AMSR-E Assuming AMSR precipitation is correct--over ocean

AMSR-ECalibrated

AIRSOriginalAIRS

High-latitude Northern Hemispheresummer case, with precipitationnear the center of the swath

26 July 2006, 04:27-05:10 UTC

Original AIRS precipitation is toolight and probably too widespread.

Calibrating to AMSR-E reducesspatial coverage, but overestimatesin the heaviest rain areas.

Histogram-matching cannot “create”precipitation where it did not exist(e.g., the AMSR-E “tail”).

CALIBRATION WITH AMSR-E (cont.)

Application of CALIBRATION WITH AMSR-EExample of AIRS filling in a feature over snow where AMSR cannot reliably estimate

AMSR-E

CalibratedAIRS

16 January 2004 mm/d

16 January 2004 mm/d

Land precip featur

e

AIRS RH (%)

1000

800

600

400

200

Pressure (hPa)

CloudSat Profiling Radar

(41.0°S, 16.8°E)(61.7°S, 7.3°E)

10 July 2006, ~00:00-00:06 UTC

The A-train formation allows fornearly-coincident space/time match-upsbetween AIRS relative humidity profilesand CloudSat radar reflectivities.

Good correspondence betweenhigh/saturated deep-layer AIRS RHand high/deep CloudSat reflectivitiesin the heart of the storm system.

COMPARISONS WITH CLOUDSAT

1000

800

600

400

200

Pressure (hPa)

AIRS RH (%)

)CloudSat Profiling Radar

(76.1°N, 5.1°W)(56.7°N, 30.8°W)

26 July 2006, ~04:24-04:30 UTC

Excellent agreement betweenAIRS humidity profile and nearly-coincident CloudSat reflectivities,both in precipitating and non-precipitating clouds.

COMPARISONS WITH CLOUDSAT (cont.)

Quality flags indicate afall-back to the microwave scheme indeep clouds, where CloudSat indicatesprecipitation.

Ocean Precipitation Frequency from Various Satellite Estimates• All estimates (except GPCP Daily) are instantaneous; different footprint sizes and precipitation rate thresholds also complicate comparison

• Preliminary results indicate Cloudsat estimates reasonable and useful for adjustment of other estimates--e.g. AIRS; but large difference among Cloudsat estimates

• SSM/I and AMSR estimates fall off rapidly at high latitudes; HOAPS (SSM/I) better, but questionable at low latitude

Seasons

Winter

Winter

Summer

Summer

• Cloudsat shows higher oceanic frequencies in winter (50-70° lat.); HOAPS agrees, other estimates do not

• Cloudsat “snow possible” bigger in winter, especially in N.H.

• HOAPS tropical features very different from AMSR and SSM/I

• AMSR may have ice “problem” at higher latitudes in winter

Currently working on time-space scale issues so we can better use Cloudsat and AMSR to determine “correct” fraction

Conclusions and Future• Research in progress--developing comparisons of various high

latitude precipitation estimates and empirical AIRS/TOVS technique to merge multiple estimates for globally-complete, high-time resolution precipitation analysis

• Cloudsat, AMSR and AIRS “simultaneity” key to much of analysis

• Cloudsat precipitation estimates (from L’Ecuyer, Haynes--CSU) very useful--but need to develop techniques to compare with other estimates--with larger footprints (and 2-d)--also which “certain”, “probable” or “possible” versions

• High latitude (especially land) precipitation still challenging--need many approaches and comparisons