ali behrangi - cnripwg/meetings/bologna-2016/... · ali behrangi nasa jet propulsion laboratory,...

Cold region precipitation estimate: Insights from multi-sensor multi-platform instruments

Ali Behrangi NASA Jet Propulsion Laboratory,

California Institute of Technology

Thanks to M. Richardson, G. Huffman, R. Adler, G. Stephens

National Aeronautics and

Space Administration

Jet Propulsion Laboratory


Pasadena, California




8th IPWG and 5th IWSSM Joint Workshop Bologna, 3-7 October, 2016

• Cold region: High latitude and high altitude • Problem: Highest precipitation uncertainty • Importance: Global water budget and regional hydrology

• Growing interest: very important in a changing climate - Poles and high altitudes warm faster than other regions • Challenges: Light rainfall, snowfall, frozen land,… • Limitation: Sparse and unreliable ground observations • No focused mission: Little attention prior to GPM • etc.

Introduction :





Zonal distribution of precipitation phase occurrence (Based on CloudSat footprint observations for 2007–09)

Ocean Land

Precipitation frequency and phase

Behrangi et al. J. of climate (2014)

Behrangi et al. WRR (2014)

Rainfall is not the dominant type of precipitation Poleward of ~50 deg latitude





TRMM era





0 1.2 2.4 3.6 mm/day 0 0.1 0.2 0.3 0.4 0.5 Fraction

Missing precipitation over ocean (TRMM era)

Behrangi et al. (JGR; 2012)





MW combined (TRMM era)

MCTA V2 GPCP

Ocean

mm

/day

Zones of discrepancy over ocean

MCTA : Merged CloudSat ,TRMM PR & AMSR (Behrangi et al. , 2014)





Comparison of precipitation detectability as a function of cloud type Fraction of precipitation detected by CloudSat

Behrangi et al. 2014

Missing precipitation over land (TRMM era)

LAND

Over land : MW precip. mainly captures: • Convective system • Rainfall over non-frozen land





Status of high latitude precipitation in various products

SH

?

Behrangi et al. 2016 (JGR)





Land+ Ocean Ocean Land (Antarctica)

Behrangi et al. 2016 JGR

Summary of statistics for Antarctic and Southern ocean

CloudSat, GPCP, and ERA-I were found fairly consistent in capturing total high

latitude precipitation. However, regional and seasonal differences could be large.





Status of high latitude precipitation in various products

(2007-2010)

NH v v

v

v

Behrangi et al. 2016 (JGR)





Behrangi et al. (JGR, 2016)

An insight from GRACE !

• GRACE supports CloudSat estimate

• Over correction of gauge undercatch might be the issue





Behrangi et al. (to be submitted)

Using GRACE to constrain precipitation amount over cold regions

GRACE

GPCP

CloudSat snowfall





Mountainous West U.S. : Orography + Snow+ AR

Satellite + gauge

Radar + gauge

Satellite only

Interpolated Gauge (PRISM)





GPM era





Zonal distribution: DPR over ocean (201404-201503)

• DPR products commonly underestimate at high latitudes compared to GPCP and MCTA • Ka nd KaHS does not increase precipitation at high latitudes • Ku and KuMS show higher precip. rate compared to other DPR products. • Ku and KuMS show relatively large jump over SH subsidence zone • DPR and DPR.GMI (2BCMB) are fairly consistent

GPCP

Ocean

mm

/day

?





• GPM products commonly underestimate at high latitudes compared to GPCP and MCTA • Products are fairy consistent over tropics • IMERG is underestimating over ocean

Zonal distribution: multi-sensor over ocean (1 year)

Ocean

mm

/day





• ATMS and AMSR are outliers in the tropics (over estimating ? ) [ if true global underestimate : 6% 11% ! ] • MHS shows better match with MCTA over ~ 30-40 S/N but then follows other

MW estimates

Zonal distribution over ocean (1 year ; A-train orbit)

Ocean

mm

/day





LAND

Zonal distribution over LAND (1 year ; MULTI-sensor)

• IMERG, TRMM 3B43, and GPCP are almost identical ( as expected)

• GPCC diverges from GPCP in high latitudes.

• DPR.GMI (CMB) products are much larger than GPCP in the tropics and 20S-40S, but start to underestimate (relative to GPCP/GPCC) poleward of lat. 50deg

mm

/day





LAND

Zonal distribution over LAND (1 year ; DPR)

• DPR, Ka, and KaHS largely under estimate !

mm

/day





LAND

Zonal distribution over ocean (1 year ; A-train time)

• MHS shows large underestimation poleward of ~ 30 deg S/N compared to GPCP/GPCC

mm

/day





Maps of difference (1 year)

CMB (DPR.GMI ) minus GPCP

• DPR.GMI under estimates in high latitudes • Does DPR.GMI over estimates over land?





IMERG - GPCP

Maps of difference (1 year)

IMERG underestimates over ocean?





• Further improvements over high latitudes and cold regions is needed (e.g., precipitation is largely underestimated)

• Overall, GPCP performs reasonably in high latitudes, but regional and seasonal differences from “real” precipitation may be large (e.g., southern ocean, Eurasia,… )

• GRACE can provide useful insights over cold land and mountainous regions

• ECMWF preforms well over high latitudes

Summary

Thanks!

[email protected]

ali behrangi - cnripwg/meetings/bologna-2016/... · ali behrangi nasa jet propulsion laboratory,...

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