GSWP-2 Evaluation

There will be three main modes of in situ evaluation of participating LSSs:

Field campaigns – The ISLSCP2/GSWP2 period overlaps a number of relevant field campaigns, which can provide validation data. Comparison of measured meteorological variables with the reanalysis-based forcing data will also provide a validation of those products.
Observational networks and long-term monitoring – There are also long-term monitoring networks of soil moisture, radiative and turbulent fluxes that can provide local or regional validation for LSSs.
Streamflow – Runoff fluxes from LSSs will be routed with a common river model to compare with streamflow measurements across a large portion of the globe. This analysis can also uncover problems in the forcing data at basin scales.

In situ data from selected field campaigns and observational networks (table below) has been converted to the ALMA convention and posted on the COLA GrADS-DODS Server (GDS) for use in model evaluation. If you would like to see other specific observational data sets converted to the ALMA convention and posted, please let us know about them!

Source	Acknowledgement / Contact		Points	Time range	Data http://www.monsoondata.org: 9090/dods/gswp/field/
First ISLSCP Field Experiment (FIFE)	Betts, A. K., and J. H. Ball, 1998: FIFE surface climate and site-average dataset:1987-1989. J. Atmos Sci , 55, 1091-1108.		1	1 May 1987 - 10 November 1989	fife
HAPEX-Sahel	HAPEX-Sahel Experiment, Steven Prince and Pavel Kabat (the scientists who collected the WCSS data)		4	19 Aug - 11 Oct 1992	hapex
Soil Climate Analysis Network (SCAN)	Bruce Newton (Acting Director, National Water and Climate Center)		21	Nov 1994 - Dec 1995	scan
Global Soil Moisture Data Bank	Robock, A., K. Ya. Vinnikov, G. Srinivasan, J. K. Entin, S. E. Hollinger, N. A. Speranskaya, S. Liu, and A. Namkhai, 2000: The Global Soil Moisture Data Bank. Bull. Amer. Meteorol. Soc., 81, 1281-1299.	China	43	1981-1992	china
		Illinois	19	1986-1995	illinois
		Iowa	1	1986-1995	iowa
		India	10	1986-1995	not available online
		Mongolia	42	1964-1993	mongolia
		Russia (AGRO)	102	1986-1995	fsuagro
		Russia (Valdai)	3	1986-1995	fsuvaldai
GEWEX Asian Monsoon Experiment (GAME) Dataset for Water and Energy Cycle in Siberia Version 1	Rikie Suzuki (Frontier Research System for Global Change) Note: Locations for GAME measurement sites in these data sets as well as citation and contact information are listed in this Excel file.	Baseline Meteorological Data in Siberia (BMDS), Ground surface and soil temperature in Siberia (GSSTS)	77	1985-2000	BMDS_GSSTS
		Hydrological and Ice Regime Data of Rivers in Eastern Siberia (HIRDR)	106	1986-1992	HIRDR_Qday
				1950-1988	HIRDR_Qmonth
				1950-1992	HIRDR_WT_day
				1949-1988	HIRDR_freeze_yr
				1986-1988	HIRDR_ice_day
				1950-1992	HIRDR_ice_mon
		Soil water at Agricultural Stations in Russia and ex-USSR (SWAS)	951	1992-1996	SWAS_Russia
		Snow Depth and Density at Agricultural Stations in Russia (SnAS)	1155	1992-1996	SnAS_Russia

Points for GAME sites are listed in this Excel file.

	FIFE		HAPEX		SCAN
Point #	lon	lat	lon	lat	lon	lat
1	-96.53	39.05	2.51	13.54	-104.44	40.52
2			2.51	13.54	-84.25	30.18
3			2.51	13.54	-81.38	29.06
4			2.57	13.55	-83.26	33.53
5					-89.54	40.19
6					-87.5	37.06
7					-76.55	39.15
8					-93.57	45.25
9					-89.05	32.2
10					-109.48	48.29
11					-76.39	35.52
12					-100.54	46.47
13					-96.28	40.51
14					-105.25	34.15
15					-77.02	42.53
16					-83.27	39.57
17					-102.06	35.1
18					-95.59	30.05
19					-119.01	46.26
20					-88.35	45.28
21					-104.09	42.04

	Illinois		Iowa		Mongolia		China
Point #	lon	lat	lon	lat	lon	lat	lon	lat
1	-88.22	40.05	-95.6	41.2	102.47	46.16	126.65	51.72
2	-88.67	37.45			91.38	46.07	130.4	48.85
3	-88.95	38.95			100.41	46.08	126.12	46.67
4	-90.83	39.8			113.17	46.41	127.36	46.08
5	-88.85	41.85			110.36	48.37	130.28	46.8
6	-90.73	40.92			102.1	44.42	132.2	46.3
7	-89.52	40.7			118.37	47.37	126.77	45.75
8	-89.62	39.52			91.39	48.01	130.54	46.8
9	-89.88	38.52			102.49	49.23	132.96	45.75
10	-89.23	37.72			106.17	45.46	85.8	44.25
11	-88.1	38.73			103.33	44.05	89.25	42.8
12	-89.67	42.28			110.07	44.54	77.25	38.47
13	-88.92	38.13			98.17	48.44	107.41	40.75
14	-88.17	40.95			92.05	48.5	105.38	39.1
15	-89.9	40.3			89.58	48.58	106.23	38.25
16	-90.15	40.97			96.51	47.45	113.8	35.16
17	-88.38	38.38			105.59	49.28	123.97	44.25
18	-88.23	40.08			104.3	47.23	128.2	43.4
19	-88.67	37.45			106.4	49.45	125.63	42.55
20					102.49	49.23	119.7	41.38
21					105.24	49.09	122.8	41.97
22					102	49.37	124.28	41.3
23					103.3	50.2	123.28	40.28
24					105.25	48.16	124.78	40.72
25					110.38	47.19	121.7	39.1
26					105.95	50.06	101.5	30.05
27					106.5	48.71	104.26	23.35
28					96.15	46.24	111.03	34.05
29					103.33	48.49	113.65	34.72
30					113.4	48.4	112.58	33.03
31					101.28	47.27	114.45	33.75
32					114.33	48.05	114.02	33
33					104.25	43.35	110.3	25.33
34					100.1	49.38	117.15	34.28
35					110.38	47.19	116.97	33.67
36					106.57	47.23	119.48	32.18
37					105.54	48.31	109.38	24.47
38					94.24	49.39	106.6	23.9
39					118.37	47.37
40					102.5	47.12
41					102	49.37
42					106.04	48.55

	FSU Agro		FSU Valdai
Point #	lon	lat	lon	lat
1	34.6	67.9	33.1	57.6
2	43.92	61.87	33.1	57.6
3	52.2	61.38	33.1	57.6
4	40.87	59.74
5	33.6	62.2
6	32	59.75
7	29.05	57.3
8	32.35	58.25
9	34.85	57.05
10	33.03	55.08
11	21.4	54.75
12	37.58	55.63
13	33.82	53.07
14	36.42	52.85
15	39.32	52.63
16	41.58	52.53
17	36.27	51.67
18	37.27	50.82
19	40.23	50.9
20	35.4	54.37
21	37.57	53.7
22	39.08	57.78
23	40.27	54.23
24	40.53	56.13
25	43.1	58.33
26	42.05	57.2
27	44.57	56.15
28	49.72	57.92
29	48.42	56.65
30	47.13	55.42
31	44.58	54.35
32	53	57.2
33	50.57	55.27
34	47.52	53.75
35	44.48	53.27
36	50.6	53.33
37	47	51.63
38	55.08	52.17
39	43.82	49.62
40	41.25	47.72
41	47.75	47.1
42	43.63	46.4
43	39.58	45.57
44	43.7	43.7
45	43.18	44.92
46	44.28	43.12
47	40.34	44.56
48	41.77	43.75
49	46.07	43.32
50	45.05	43.32
51	47.22	44.7
52	33.95	51.18
53	33.8	49.75
54	36.55	49.65
55	37.8	48.08
56	38.87	49.03
57	31.82	48.42
58	35.98	47.08
59	34.67	48.17
60	31.98	51.4
61	30.52	50.3
62	31.32	49.18
63	28.28	50.87
64	28.6	49.07
65	27	49.42
66	25.53	49.53
67	26.68	48.47
68	24.05	49.88
69	24.52	48.75
70	24.9	51.2
71	26.17	50.75
72	22.93	48.5
73	29.87	46.4
74	31.78	47.38
75	33.52	46.63
76	34.15	45.22
77	28.85	46.82
78	27.62	53.82
79	30.62	53.68
80	28.82	55.12
81	25.1	53.62
82	25.25	52.47
83	29.72	52.3
84	25.6	58.62
85	25.27	56.82
86	23.88	55.3
87	44.65	43.76
88	47.58	42.5
89	44.98	42.37
90	49.97	50.35
91	48.8	47.9
92	57.95	49.57
93	63.37	53.05
94	68.18	54.55
95	69.6	53.3
96	70.17	51.75
97	73.07	50.17
98	69.7	48.03
99	75.97	52.98
100	80.65	48.93
101	83.58	49.45
102	64.57	45.25
103	68.77	42.57
104	72.57	43.82
105	77.08	43.72
106	79.02	45.2
107	54.38	45
108	65.58	50.48
109	73.18	40.32
110	75.22	41.52
111	77.94	42.14
112	74.68	42.88
113	72.55	42.18
114	72.62	41.25
115	54.67	39.08
116	58	38
117	62.15	37.37
118	63.6	39.08
119	57.95	41.63
120	59.15	43.27
121	60.38	41.4
122	64.12	41.1
123	67.49	38.09
124	66.12	38.81
125	66.47	39.85
126	68.08	40.63
127	67.59	40.27
128	69.76	41.13
129	71.1	41.02
130	72.07	40.57
131	71.93	40.68
132	65.5	40.6
133	71.6	36.72
134	68.76	39.44
135	69.3	38.7
136	69.66	38.09
137	68.08	37.69
138	68.65	38.5
139	55.43	57.8
140	62.08	57.32
141	60.8	54.42
142	64.75	55.38
143	56.15	54.23
144	68.18	56.72
145	73.4	55.28
146	84.38	56.77
147	80.12	54.4
148	86.78	54.98
149	83.17	52.2
150	92.95	55.7
151	94.6	51.48
152	90.67	53.43
153	103.2	54.62
154	115.27	51.07
155	108.5	52.05
156	109.7	53.05
157	62.47	70.92
158	71.88	69.02
159	55.33	79.87
160	92.2	76.18
161	125.73	61.8
162	162.4	70.13
163	176.58	68.77
164	133.66	44.42
165	136.5	50.33
166	129.25	51.75
167	142.73	47.05
168	142.68	49.35
169	126.3	61.52
170	158.57	55.05
171	148.95	60.95