Warming trends in the Himalaya

Willis Eschenbach at WUWT once again found something that he couldn't believe. The Himalayas are warming rapidly. There's an IPCC claim that warming in lower areas of Nepal may be about 0.4 C/dec, and in higher areas 0.9 C/decade.

Willis' post got sidetracked into fussing about GISS adjustments to 20 years of data at Katmandu. But a comment on the thread was right to the point. The IPCC was relying on a paper by Shrestha et al which had looked through records of 49 stations in Nepal in finding that result.

Zeke Hausfather at the Blackboard looked at GSOD data. This is a more plentiful data set derived from SYNOP forms. It is unadjusted, but does not go as far back in time. He found there was also a strong warming trend. His analysis was based mainly on Katmandu. He also pointed out that the IPCC did not use GISS adjusted data.

So I thought I could use TempLS and the GSOD database to look at Nepal and even beyond in the Himalaya. TempLS also allows us to look at different altitude ranges, subject to station availability. Willis found only one GHCN station in Nepal - GSOD has 12, but some with short histories. Anyway, here's the analysis. Most of the trends are since 1979; data histories get sparse before then.

Update: Zeke pointed out a bug. My first diagnosis (below) was wrong. The problem was not in the analysis program but in the GSOD datafile, as modified by my preprocessor. The GSOD database is not as tidy as GHCN, and some data refer to stations not in the inventory. In the process of fixing that, a block of stations (including Nepal) got displaced by 1. This doesn't affect the analysis, but does affect the selection - you don't get the right stations. For countries, the effect is small because they are consecutive, so only one station is wrongly chosen. But for an altitude spec, it's more serious.

The Nepal trends are little changed, and Himalaya increase a bit. The two Hi sets just have too many gaps for an analysis to work, so I've dropped them.

Earlier update. Zeke, in the comments has pointed out a bug. It seems to be in the new multi-run capability of ver 2, and to affect small datasets where sometimes no information at all exists in a particular month. So the HiNepal results are invalid, and I'm checking HiHimal. I believe the Nepal and Himalaya results are unaffected.

First, an overview of the region in Google Earth, using the KMZ files described here. The rural stations are green, urban yellow, small towns brown, and the big pushpins have 50 years data recorded (very small <20 years). The sparsest section is actually India.

 

Nepal

The first analysis is just the country Nepal. Here are the stations (numbers and maps) and plots:

Himalaya

The next analysis is of the Himalayas generally, defined as anywhere in Nepal, India or Pakistan N of a line given by 14*Lat+8*lon>1046 and above 1000m. For those interested in working TempLS, the specifying expression is:
mask=expression({a=tv$country;(a==217 | a==219 | a==207) & tv$alt>1000 & 14*tv$lat+8*tv$lon>1046});

Trends

Finally, here is the collected table of trends (C/decade) since 1980 and since 1990:

Trend	Nepal	Himalaya
Number	12	24
1980-2009	0.7747	0.6053
Trend_se	0.132	0.1041
1990-2009	1.003	0.8847
Trend_se	0.2804	0.1832

Here is the earlier set of trends, which used the incorrect input data:

Trend	NepalGSOD	HiNepal	Himalaya	HiHimal
Number	12	2	24	7
1980-2009	0.7723	0.7146	0.5036	0.5642
Trend_se	0.1323	0.1438	0.1019	0.1076
1990-2009	1.006	1.018	0.7467	0.8267
Trend_se	0.281	0.3006	0.1947	0.2113

Conclusion

Being able to analyse various selected subsets means that we get a feel for how regional variations might affect the conclusion that the area is warming. All these subsets show it to a marked degree. No sub-region has a rate less than 0.5 C/decade (5 deg/century).

Update. Here is a list of the stations in the Himalaya set with some metadata.

urban: A=rural, C=urban, B=small town

country: 207=India 217=Nepal 219=Pakistan

length: Number of years with atleast one month record

Name	country	alt	startyr	endyr	length yrs	urban	lat	lon
SRINAGAR	207	1587	1973	2010	38	C	34.08	74.83
SHIMLA	207	2202	1973	1973	1	C	31.1	77.17
KULLU MANALI	207	1089	2005	2005	1	A	31.88	77.18
DADELDHURA	217	1865	1978	2001	8	A	29.3	80.58
JUMLA	217	2300	1990	2001	10	A	29.28	82.17
KATHMANDU AIRPORT	217	1337	1976	2010	35	C	27.7	85.37
SYANGBOCHE	217	3700	1976	1979	4	A	27.82	86.72
OKHALDHUNGA	217	1720	1976	2001	12	A	27.3	86.5
TAPLEJUNG	217	1732	1978	2001	11	A	27.35	87.67
DHANKUTA	217	1210	1976	2008	32	A	26.98	87.35
GUPIS	219	2156	2006	2009	4	A	36.17	73.4
CHITRAL	219	1500	1973	2010	22	A	35.85	71.83
DIR	219	1370	1980	2010	12	A	35.2	71.85
DROSH	219	1465	1957	2010	42	A	35.57	71.78
GILGIT	219	1459	1973	2009	11	B	35.92	74.33
SKARDU	219	2181	1975	2009	13	A	35.3	75.68
BUNJI	219	1470	2005	2009	5	A	35.67	74.63
CHILLAS	219	1251	2005	2009	5	A	35.42	74.1
ASTORE	219	2168	2005	2009	5	A	35.37	74.9
CHITRAL	219	1500	2005	2005	1	A	35.88	71.8
BATTAL	219	1676	1975	1976	2	A	34.58	73.15
KAKUL	219	1309	1973	2010	19	C	34.18	73.25
CHERAT	219	1372	2005	2009	5	A	33.82	71.88
MURREE	219	2127	1973	2010	15	C	33.92	73.38