# Presentation: 663820

## HIRS Observations of Clouds since 1978

**Donald P. Wylie & W. Paul Menzel **
**Cooperative Institute for Meteorological Satellite Studies**
**NOAA/NESDIS**
**University of Wisconsin-Madison**
**Madison, Wisconsin,USA**
**Darren Jackson**
**Environmental Technology Laboratory, NOAA/OAR**
**Boulder, Colorado, USA**
**John Bates**
**National Climate Data Center**
**Asheville, North Caroline USA**
**CO2 Slicing Method**
**22 year stats**
**Effects of orbit drift, CO2 increase, and sensor changes**
**16 year trends**
**Comparison with ISCCP and GLAS**
**October 2004**

## Climate System Energy Balance 

**Climate System Energy Balance **

## Rationale for Cloud Investigations

- clouds are a strong modulator of shortwave and longwave; their effect on global radiative processes is large
-   (1% change in global cloud cover equivalent to about 4% change in CO2 concentration)
- accurate determination of global cloud cover has been elusive
-   (semi transparent clouds often underestimated by 10%)
- global climate change models need accurate estimation of cloud cover,
- height, emissivity, thermodynamic state, particle size
-   (high/low clouds give positive/negative feedback to greenhouse effect, and
-     higher albedo from anthropogenic aerosols may be negative feedback)
- there is a need for consistent long term observation records to enable
- better characterization of weather and climate variability
-   (ISSCP is a good start)

## Why are clouds so tough?

- Aerosols <0.1 micron, cloud systems >1000 km
- Cloud particles grow in seconds: climate is centuries
- Cloud growth can be explosive:       1 thunderstorm packs the energy of an H-bomb.
- Cloud properties can vary a factor of 1000 in hours.
- Few percent cloud changes drive climate sensitivity
- Best current climate models are 250 km scale
- Cloud updrafts are a 100 m to a few km.

## Cirrus detection has been elusive in the visible bands

**Cirrus detection has been elusive in the visible bands**

**Depending on view angle GOES sees or misses Texas cirrus**

## IR window sees cirrus but cannot place height correctly

**IR window sees cirrus but cannot place height correctly**

## Two unknowns, N and Pc ,

**Two unknowns, N******** and P****c ****,**
**require two measurements**

**Radiance from a **
**partly cloudy FOV**

- R=[1- **N******]Rclear air + **N****** Ropq cld (**P****c**)

## CO2 slicing corrects for semi-transparency of cirrus 

**CO2 slicing corrects for semi-transparency of cirrus**

## RTE in Cloudy Conditions

- 	Iλ  =  η Icd + (1 - η) Iclr     where cd = cloud, clr = clear, η = cloud fraction
-  	             λ                           λ
- 			     o
- 	Iclr  =  Bλ(Ts) λ(ps) +     Bλ(T(p)) dλ .
- 	 λ                               ps
- 	                                                       pc
- 	Icd  =  (1-ελ) Bλ(Ts) λ(ps) + (1-ελ)      Bλ(T(p)) dλ
-      	 λ			           ps
- 						         o
-    				 + ελ Bλ(T(pc)) λ(pc) +     Bλ(T(p)) dλ
-                                    				        pc
- ελ is emittance of cloud.  First two terms are from below cloud, third term is cloud contribution, and fourth term is from above cloud.  After rearranging
- 			          pc           dBλ
- 		Iλ - Iλclr  =  ηελ      (p)  _        _   dp  .
-     	  		         ps             dp

## Cloud Properties from CO2 Slicing

- RTE for cloudy conditions indicates dependence of cloud forcing (observed minus clear sky radiance) on cloud amount () and cloud top pressure (pc)
- 	                              pc
- 	(I - Iclr)  =          dB .
- 	                             ps
- Higher colder cloud or greater cloud amount produces greater cloud forcing; dense low cloud can be confused for high thin cloud.  Two unknowns require two equations.
- pc can be inferred from radiance measurements in two spectral bands where cloud emissivity is the same.   is derived from the infrared window, once pc is known.

## CO2 channels see to different levels in the atmosphere

**CO2 channels see to different levels in the atmosphere**

- 14.2 um             13.9 um             13.6 um           13.3 um

## Different ratios 

**Different ratios **
**reveal cloud properties **
**at different levels**
**hi - 14.2/13.9**
**mid - 13.9/13.6**
**low - 13.6/13.3**
**Meas          Calc**
**	****            ****p****c****	**
**(I********1****-I********1****clr****)    ************1**** ******** ************1**** dB********1**
**	****            ****p****s**
**----------- = ----------------**
**	****            ****p****c****	**
**(I********2****-I********2****clr****)    ************2**** ******** ************2**** dB********2**
**	****            ****p****s**

## Slide 13

## Determining Cloud Presence and Properties

- Detect clouds where (I - Iclr)  > 1 mW/m2/ster/cm-1
- 	in IRW or CO2 channels
- Use CO2 Slicing Method to estimate pc
- 	pc selected best satisfies RTE for all bands
- Estimate IRW using IRW radiances
- If no CO2 bands qualify, IRW estimates opaque cld pc
- If too low in atmosphere, declare FOV clear

## Ratio of measured cloud signal 

**Ratio of measured cloud signal **
**for spectrally close bands yields Pc**

## Slide 16

## UW NOAA Pathfinder HIRS global cloud statistics from December 1978 through December 2001

**UW NOAA Pathfinder HIRS global cloud statistics from December 1978 through December 2001**

## UW NOAA Pathfinder HIRS global cloud statistics from December 1978 through December 2001

**UW NOAA Pathfinder HIRS global cloud statistics from December 1978 through December 2001**
**(corrected for higher cloud obstruction of lower clouds using random overlap assumption)**

## Slide 19

## How Cloudy is the Earth?

- GLAS 22 Feb – 28 Mar 2003, HIRS 1979 – 2001, ISCCP 1983 – 2001,
- SAGE 1985-89, Surface Reports 1980-89, CLAVR 1982 - 2004
- ISCCP reports 7-15% less cloud than HIRS because it misses thin cirrus.
- HIRS and GLAS report nearly the same high cloud frequencies.
- HIRS reports more clouds over land than GLAS probably because GLAS
- sees holes in low cumulus below the resolution of HIRS.

**CLAVR**

**60**

## GLAS

## All Cloud Observations from GLAS vs HIRS

**GLAS**

**HIRS**

## HIRS minus GLAS All Cloud Difference

**HIRS Frequency of All Clouds**
**during the period of GLAS**

- GLAS finds more tropical clouds over oceans where HIRS reports <40%.
- GLAS finds less clouds in polar regions and western tropical Pacific.

## HIRS minus GLAS High Cloud Difference

- HIRS Frequency of High Cloud

- HIRS – GLAS Difference

- GLAS > HIRS    HIRS > GLAS

- HIRS reports more high clouds in parts of tropics and southern hemisphere, but areas of differences are scattered and not meteorologically organized.

## Looking at animation of monthly means for 1997

## HIRS-GLAS by latitude

- HIRS under detection is mainly over oceans.

## Inferring Decadal HIRS Cloud Trends

**	****requires corrections for**
**	****(1) anomalous satellite data or gaps**
**	****(2) orbit drift ****	**
**	****(3) CO2 increase **
**	****       ****constant CO2 concentration was assumed in analysis**

## Used only 2 am/pm orbit data after 1985 in cloud trend analysis for continuity of data and satellite to satellite consistency

- Satellite by satellite analysis
- Gap in 8am/pm orbit coverage between NOAA-8 and -10
- HIRS cloud trends show unexplained dip with NOAA-7 in 2 am/pm orbit.

## Measurements from 9 sensors used in 22 year study of clouds

- NOAA 6 HIRS/2				NOAA 5 HIRS
- NOAA 8 HIRS/2				NOAA 7 HIRS/2
- NOAA 10 HIRS/2			NOAA 9 HIRS/2
- NOAA 12 HIRS/2			NOAA 11 HIRS/2I *
- 					NOAA 14 HIRS/2I *
- HIRS/2I ch 10 at 12.5 um instead of prior HIRS/2 8.6 um.  Asterisk indicates orbit drift
- from 14 UTC to 18 UTC over 5 years of operation

**Measurements from 9 sensors used in 22 year study of clouds**

**Some sensors experienced significant orbit drift**

## all 2 am/pm satellites adjusted linearly to represent data for ascending node at 1400 hrs local time 

- all 2 am/pm satellites adjusted linearly to represent data for ascending node at 1400 hrs local time

## (From Engelen et al., Geophys Res Lett, 2001)

- Atmospheric CO2 has not been constant

## SARTA calculations: BT with 360 ppmv minus BT with 340,345,...380 ppmv

## HIRS cloud trends have been calculated with CO2 concentration assumed constant at 380 ppm. 

- Lower CO2 concentrations increase the atmospheric transmission, so radiation is detected from lower altitudes in the atmosphere.
- For January and June 2001 the clouds detected by NOAA 14 in the more transparent atmosphere (CO2 at 335 ppm) are found to be lower by 13-50 hPa
- dry(335,p,ch) = dry(380,p,ch)**{335/380)
- (p,ch) = dry(p,ch)*H2O(p,ch)*O3(p,ch).** **
- More transparent atmosphere (CO2 at 335 ppm) results in HIRS reporting clouds lower by 15-50 hPa with 2% less high clouds than in the more opaque atmosphere (CO2 at 380 ppm); this implies that the frequency of high cloud detection in the early 1980s should be adjusted down.
- Cloud time series was adjusted to represent a linear increase of CO2 from 335 ppm in 1979 to 375 ppm in 2001

## Slide 34

## Slide 35

## Slide 36

## Slide 37

##  4

**Wielicki et al (2002) CERES deviation of reflected shortwave flux wrt 1985-89 mean for 20N-20S**** **

** ****4**
** ****2**
** ****0**
**-2**

- HIRS deviation of hi cloud detection wrt 1978-88 mean

## Conclusions

-  clouds were found in 75% of HIRS observations since 1978
- 	(hi clouds in 33%)
-  good agreement with GLAS
-  ISCCP finds 10-15 % fewer high and all clouds
-  loop of monthly means shows latitudinal cloud cover follows the sun
-  16 yr trends in HIRS high cloud statistics reveal modest 2% increase
- 	during last decade compared with previous decade
-  orbit drift, CO2 increase, and satellite to satellite differences 	were mitigated
-  ISCCP shows decreasing trends in total cloud cover of 3 to
- 	4 % per decade but little high cloud trend