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Annex A. Agroclimatic indicators and BIOMSS

Table A.1. January-April 2016 agroclimatic indicators and biomass byglobal Monitoring and Reporting Unit

		RAIN	TEMP	RADPAR	BIOMSS	RAIN	TEMP	RADPAR	BIOMSS
	65 Global MRUs	Current (mm)	15YA dep. (%)	Current (°C)	15YA dep. (°C)	Current (MJ/m2)	15YA dep. (%)	Current (g DM/m2)	5YA dep. (%)
1	Equatorial central Africa	494	-6	26.3	0.3	1176	4	1492	2
2	East African highlands	181	-20	21.1	0.1	1269	0	657	0
3	Gulf of Guinea	190	0	28.6	-0.5	1242	2	654	3
4	Horn of Africa	350	-3	24.9	-0.3	1263	0	993	3
5	Madagascar (main)	882	-13	24.8	-0.6	1088	1	1813	-7
6	Southwest Madagascar	376	-28	25.1	-1.2	1269	6	1144	-17
7	North Africa-Mediterranean	74	-54	12.7	0.5	983	2	289	-44
8	Sahel	29	21	29.6	-0.5	1364	0	97	26
9	Southern Africa	483	-4	24.9	0.3	1211	3	1283	-2
10	Western Cape (South Africa)	102	-7	19.6	0.0	1292	0	422	7
11	British Columbia to Colorado	275	37	-1.2	2.0	766	-2	583	28
12	Northern Great Plains	207	24	2.2	2.7	750	-6	670	25
13	Corn Belt	329	-4	1.5	1.2	715	-2	741	8
14	Cotton Belt to Mexican Nordeste	440	20	12.5	0.3	903	1	1123	14
15	Sub-boreal America	54	-58	-6.5	2.8	593	-1	387	11
16	West Coast (North America)	294	8	8.6	1.4	789	-3	781	28
17	Sierra Madre	80	14	15.7	-0.3	1268	0	295	13
18	SW U.S. and N. Mexican highlands	107	41	9.7	0.6	1080	1	395	40
19	Northern South and Central America	216	-11	26.6	-0.1	1109	2	589	-15
20	Caribbean	180	-9	24.2	-0.6	1068	-2	578	-6
21	Central-northern Andes	626	-1	18.2	0.9	1081	6	1325	-3
22	Nordeste (Brazil)	437	-5	27.9	0.4	1192	-2	1195	12
23	Central eastern Brazil	710	-7	26.3	-0.2	1126	2	1696	-8
24	Amazon	1021	-6	27.7	0.0	995	4	2090	-7
25	Central-north Argentina	583	25	24.4	-1.0	1042	-4	1492	7
26	Pampas	789	39	23.2	-0.5	1087	-5	1780	14
27	Western Patagonia	102	-28	13.2	-0.9	1156	-1	433	2
28	Semi-arid Southern Cone	218	41	17.8	-1.1	1145	-4	723	36
29	Caucasus	328	22	4.2	1.5	805	0	800	8
30	Pamir area	242	2	4.4	1.2	963	-1	575	-13
31	Western Asia	168	6	8.7	1.5	897	-2	562	1
32	Gansu-Xinjiang (China)	86	83	-1.2	1.0	883	-2	311	53
33	Hainan (China)	205	56	20.6	-1.4	906	-1	655	30
34	Huanghuaihai (China)	110	23	6.9	0.5	912	1	456	35
35	Inner Mongolia (China)	111	163	-4.4	0.0	881	1	424	99
36	Loess region (China)	94	61	3.1	0.0	923	-1	413	44
37	Lower Yangtze (China)	634	47	11.0	-0.1	716	-8	1277	24
38	Northeast China	135	84	-6.3	0.6	785	0	454	72
39	Qinghai-Tibet (China)	213	32	2.0	-0.1	1036	-3	431	8
40	Southern China	460	99	15.2	-1.1	789	-8	1027	53
41	Southwest China	211	36	9.7	-0.3	726	-8	674	30
42	Taiwan (China)	352	77	16.0	-1.5	840	-8	1185	83
43	East Asia	178	0	-1.7	0.6	787	-1	564	29
44	Southern Himalayas	191	16	19.8	0.4	1064	-2	447	-15
45	Southern Asia	67	-35	27.3	0.8	1247	1	235	-34
46	Southern Japan and Korea	388	0	7.5	0.9	780	-5	1092	10
47	Southern Mongolia	57	133	-8.4	0.0	833	-2	261	109
48	Punjab to Gujarat	41	-24	23.5	0.2	1184	0	178	-31
49	Maritime Southeast Asia	1003	-7	26.2	0.0	1002	0	1885	-12
50	Mainland Southeast Asia	88	-44	26.7	-0.2	1230	6	319	-44
51	Eastern Siberia	107	-16	-11.1	0.1	596	-3	315	1
52	Eastern Central Asia	66	38	-12.7	1.5	683	-2	267	37
53	Northern Australia	685	-17	27.2	0.0	1160	6	1454	-16
54	Queensland to Victoria	172	-23	21.9	0.3	1224	0	638	-25
55	Nullarbor to Darling	208	134	21.0	-0.7	1223	-7	796	99
56	New Zealand	164	-39	15.7	0.7	1000	-3	694	-18
57	Boreal Eurasia	216	16	-5.0	0.1	400	-7	467	3
58	Ukraine to Ural mountains	236	45	-0.1	1.9	449	-11	711	21
59	Mediterranean Europe and Turkey	225	-15	8.7	0.8	776	-3	734	-9
60	W. Europe (non Mediterranean)	270	17	5.1	0.2	544	-6	907	18
61	Boreal America	272	26	-4.2	5.1	441	-8	462	44
62	Ural to Altai mountains	128	16	-5.2	2.8	568	-6	488	24
63	Australian desert	148	52	22.5	-1.0	1283	-3	624	17
64	Sahara to Afghan deserts	97	26	17.8	-0.2	1155	-1	346	24
65	Sub-arctic America	83	171	-18.2	5.9	173	-3	72	186

Note: Departuresare expressed in relative terms (percentage) for all variables, except fortemperature, for which absolute departure in degrees Celsius is given. Zeromeans no change from the average value; relative departures are calculated as(C-R)/R*100, with C=current value and R=reference value, which is the five-year(5YA) or fifteen-year average (15YA) for the same period between January andApril.

Table A.2. January-April 2016 agroclimatic indicators andbiomass by country


		RAIN		TEMP		RADPAR		BIOMSS
	31 Countries	Current (mm)	15YA Dept (%)	Current (°C)	15YA Dept (°C)	Current (MJ/m2)	15YA Dept (%)	Current (g DM/m2)	5YA Departure (%)
[ARG]	Argentina	732	50	22.2	-0.8	1086	-5	1592	16
[AUS]	Australia	226	-13	22.3	0.1	1221	-1	701	-13
[BGD]	Bangladesh	255	23	24.1	0.4	1063	-4	614	3
[BRA]	Brazil	784	-7	26.5	-0.1	1091	1	1772	-5
[CAN]	Canada	173	-9	-4.5	2.7	620	-2	437	14
[CHN]	China	321	55	7.2	-0.1	790	-5	662	39
[DEU]	Germany	265	24	4.3	0.0	481	-7	928	20
[EGY]	Egypt	42	-28	16.8	0.5	1035	-1	202	2
[ETH]	Ethiopia	150	-19	21.9	0.2	1266	0	573	-2
[FRA]	France	252	2	6.4	-1.1	570	-8	940	31
[GBR]	United Kingdom	412	49	5.0	-1.3	450	-3	986	5
[IDN]	Indonesia	1215	3	26.3	0.0	966	-1	2167	-4
[IND]	India	97	-5	24.9	0.8	1197	0	242	-31
[IRN]	Iran	196	-2	8.4	0.9	994	-1	599	-6
[KAZ]	Kazakhstan	143	28	-3.3	3.0	620	-7	527	27
[KHM]	Cambodia	58	-67	29.0	0.0	1267	8	247	-60
[MEX]	Mexico	117	35	19.6	-0.3	1174	-1	376	24
[MMR]	Myanmar	70	-24	23.7	-0.6	1186	0	267	-26
[NGA]	Nigeria	156	12	29.0	-0.4	1293	0	447	11
[PAK]	Pakistan	142	-13	15.4	-0.1	1065	-1	357	-27
[PHL]	Philippines	125	-77	26.0	-0.1	1153	9	497	-62
[POL]	Poland	216	25	3.1	0.7	451	-10	862	17
[ROU]	Romania	274	38	5.0	1.8	606	-5	951	28
[RUS]	Russia	191	36	-3.7	2.1	505	-8	542	22
[THA]	Thailand	89	-54	27.1	-0.1	1245	8	339	-49
[TUR]	Turkey	338	13	6.1	2.0	854	2	901	6
[UKR]	Ukraine	236	35	3.2	1.8	516	-7	883	29
[USA]	USA	334	14	6.4	1.2	818	-2	811	19
[UZB]	Uzbekistan	199	2	8.4	2.2	800	-2	650	4
[VNM]	Vietnam	214	28	21.9	-0.5	981	4	593	2
[ZAF]	South Africa	299	-7	21.4	0.6	1248	3	948	-8

See note table A.1.

Table A.3. Argentina, January-April 2016 agroclimaticindicators and biomass (by province)

	RAIN		TEMP		RADPAR		BIOMSS
	Current (mm)	15YA Departure (%)	Current (°C)	15YA Departure (°C)	Current (MJ/m2)	15YA Departure (%)	Current (g DM/m2)	5YA Departure (%)
Buenos Aires	616	41	19.7	-1.0	1126	-5	1571	19
Chaco	1009	80	25.5	-0.6	1085	-6	2084	34
Cordoba	617	35	21.4	-0.9	1062	-8	1578	9
Corrientes	1065	71	24.9	-0.7	1078	-7	1923	20
Entre Rios	1039	78	23.0	-0.5	1095	-6	1734	16
La Pampa	615	62	20.1	-1.3	1134	-7	1638	31
Misiones	826	18	24.9	0.0	1079	-4	2035	11
Santiago Del Estero	517	13	24.5	-1.0	1032	-6	1476	7
San Luis	589	49	20.4	-1.4	1091	-7	1523	14
Salta	725	38	23.3	-0.7	1022	0	1577	13
Santa Fe	839	53	23.6	-0.4	1090	-6	1705	10

See note table A.1.

Table A.4. Australia, January-April 2016 agroclimaticindicators and biomass (by state)

New South Wales	154	-33	22.5	0.4	1250	1	616	-31
South Australia	131	34	19.9	-0.2	1226	-3	580	5
Victoria	119	-32	19.4	0.4	1166	-4	546	-30
W. Australia	215	72	21.6	-0.6	1232	-6	799	78

See note table A.1.

Table A.5. Brazil, January-April 2016 agroclimaticindicators and biomass (by state)

Ceara	483	-27	27.9	0.1	1114	-3	1542	3
Goias	666	-20	25.7	-0.4	1156	2	1670	-19
Mato Grosso Do Sul	783	14	26.6	-1.1	1131	-1	1928	0
Mato Grosso	991	-3	27.6	0.2	1093	5	2168	-8
Minas Gerais	534	-16	25.1	0.2	1178	1	1357	-8
Parana	652	-3	24.3	0.0	1097	2	1811	-3
Rio Grande Do Sul	830	35	23.5	-0.3	1066	-5	1975	16
Santa Catarina	703	-2	22.2	0.1	1037	-2	1865	-3
Sao Paulo	689	-8	25.3	0.1	1127	2	1786	-8

See note table A.1.

Table A.6. Canada, January-April 2016 agroclimatic indicatorsand biomass (by province)

Alberta	92	-15	-2.3	4.2	591	-4	453	6
Manitoba	89	-12	-6.5	2.9	636	-5	407	18
Saskatchewan	100	4	-4.7	3.9	617	-6	433	18

See note table A.1.

Table A.7. India, January-April 2016 agroclimaticindicators and biomass (by state)

Arunachal Pradesh	658	29	15.2	-0.3	758	-14	1202	10
Andhra Pradesh	28	-54	29.1	0.8	1279	2	119	-48
Assam	606	68	22.1	0.2	863	-9	1158	32
Bihar	47	-34	24.5	0.4	1163	-1	195	-45
Chandigarh	n.a.	n.a.	n.a.	n.a.	n.a.	n.a.	n.a.	n.a.
Chhattisgarh	72	-7	26.6	0.9	1210	0	340	-12
Daman and Diu	0	-100	26.8	1.5	1308	0	0	-100
Delhi	45	-53	22.2	0.7	1129	0	194	-64
Dadra and Nagar Haveli	5	-5	24.5	-0.9	1306	1	30	-27
Gujarat	12	86	26.7	0.5	1278	0	63	26
Goa	0	-100	26.5	-0.7	1338	1	0	-100
Himachal Pradesh	273	6	5.8	1.4	1065	-3	515	-21
Haryana	59	-46	20.9	0.3	1113	0	249	-54
Jharkhand	45	-43	25.1	1.1	1194	0	222	-41
Kerala	126	-52	28.4	0.7	1280	2	454	-42
Karnataka	20	-76	27.6	0.7	1310	2	97	-67
Meghalaya	652	46	20.2	1.3	974	-7	966	14
Maharashtra	36	-3	27.7	1.1	1289	2	175	-16
Manipur	701	118	18.0	0.5	974	-9	1164	51
Madhya Pradesh	45	-14	25.6	1.0	1229	1	201	-33
Mizoram	387	54	20.4	-0.3	1053	-7	918	39
Nagaland	434	45	17.3	0.1	899	-10	1071	32
Orissa	100	13	26.9	0.9	1198	-1	382	-8
Puducherry	15	-89	28.7	1.2	1286	5	80	-81
Punjab	89	-36	19.4	0.2	1063	0	363	-37
Rajasthan	13	-58	23.9	0.2	1204	0	70	-59
Sikkim	285	40	8.0	1.0	999	-7	604	4
Tamil Nadu	25	-79	28.6	0.3	1320	4	104	-71
Tripura	388	55	23.6	0.5	1028	-5	972	46
Uttarakhand	140	-33	12.5	2.5	1099	-1	380	-45
Uttar Pradesh	42	-51	23.6	0.9	1165	1	189	-61
West Bengal	87	-29	25.6	1.1	1128	-2	319	-37

See note table A.1.

Table A.8. Kazakhstan, January-April 2016 agroclimaticindicators and biomass (by oblast)

Akmolinskaya	116	30	-5.1	3.4	580	-7	526	43
Karagandinskaya	118	27	-4.7	3.1	652	-6	530	40
Kustanayskaya	145	44	-4.9	2.7	545	-9	551	38
Pavlodarskaya	60	-17	-5.5	2.8	594	-5	328	-1
Severo	119	25	-5.7	3.0	529	-6	502	30
Vostochno	128	2	-6.8	2.5	692	-5	418	21
Zapadno	197	63	-0.3	3.3	511	-16	727	41

See note table A.1.

Table A.9. Russia, January-April 2016 agroclimaticindicators and biomass (by oblast, kray and republic)

Bashkortostan	202	33	-3.5	3.3	473	-10	560	32
Chelyabinskaya	135	24	-5.2	2.1	487	-9	514	29
Gorodovikovsk	n.a.	n.a.	n.a.	n.a.	n.a.	n.a.	n.a.	n.a.
Krasnodarskiy	174	-13	-2.1	1.2	572	-2	556	3
Kurganskaya	118	22	-5.5	2.4	477	-11	523	29
Kirovskaya	226	40	-3.6	2.4	401	-7	535	20
Kurskaya	298	83	0.5	1.5	447	-17	753	16
Lipetskaya	318	96	0.0	2.1	424	-21	720	21
Mordoviya	297	94	-1.4	2.5	434	-13	646	24
Novosibirskaya	99	-3	-7.0	3.0	514	-6	456	23
Nizhegorodskaya	276	77	-1.9	2.1	418	-9	619	22
Orenburgskaya	210	48	-2.8	3.2	505	-13	603	32
Omskaya	100	-2	-6.6	3.0	501	-6	478	25
Permskaya	211	35	-4.4	3.1	392	-11	513	24
Penzenskaya	287	84	-1.0	2.9	442	-17	670	27
Rostovskaya	212	1	3.7	2.4	529	-10	841	18
Ryazanskaya	290	78	-0.8	2.2	420	-14	676	21
Stavropolskiy	268	37	5.3	2.1	613	-3	854	18
Sverdlovskaya	142	26	-5.2	2.5	420	-11	505	21
Samarskaya	203	42	-2.0	3.1	479	-12	636	29
Saratovskaya	226	57	-0.3	3.0	480	-18	721	29
Tambovskaya	323	102	0.0	2.9	427	-21	726	25
Tyumenskaya	104	4	-6.0	3.0	476	-7	502	25
Tatarstan	209	46	-2.6	2.8	462	-9	596	27
Ulyanovskaya	205	43	-2.0	2.8	468	-11	627	27
Udmurtiya	225	48	-3.4	3.0	406	-11	546	25
Volgogradskaya	240	54	1.9	2.8	488	-18	838	29
Voronezhskaya	276	73	1.7	3.1	458	-17	826	29

See note table A.1.

Table A.10. UnitedStates, January-April 2016 agroclimatic indicators and biomass (by state)

Arkansas	705	49	10.9	0.8	843	1	1320	3
California	259	16	9.5	1.4	891	-3	683	32
Idaho	311	84	0.2	1.5	794	-1	710	31
Indiana	360	-5	4.8	1.1	751	-3	1009	12
Illinois	272	-21	4.8	1.3	760	-4	953	7
Iowa	267	6	2.2	1.7	734	-8	842	18
Kansas	210	7	7.0	1.7	889	1	627	-1
Michigan	313	7	-0.1	1.3	644	-9	669	12
Minnesota	260	49	-1.9	2.4	658	-10	623	25
Missouri	348	-6	7.2	1.4	805	0	1040	1
Montana	243	116	1.1	3.1	713	-7	747	51
Nebraska	219	37	4.0	2.2	822	-4	805	31
North Dakota	229	113	-1.4	3.7	663	-12	636	47
Ohio	366	5	4.2	1.3	729	-2	971	12
Oklahoma	371	33	10.1	0.9	927	4	860	4
Oregon	335	33	5.3	1.6	698	-3	900	35
South Dakota	257	85	1.9	3.0	730	-9	797	41
Texas	319	42	14.0	0.3	977	3	792	35
Washington	313	24	4.9	1.8	645	0	898	29
Wisconsin	296	13	-0.8	1.5	657	-9	672	16

See note table A.1.

Table A.11. China, January-April2016 agroclimatic indicators and biomass (by province)

Anhui	332	5	9.7	0.2	810	-4	1018	22
Chongqing	275	47	9.5	0.0	609	-8	900	50
Fujian	871	85	11.9	-0.7	688	-14	1504	45
Gansu	769	131	15.4	-1.2	682	-13	1513	74
Guangdong	77	45	1.8	0.0	936	-2	306	22
Guangxi	574	96	14.6	-0.7	640	-8	1153	42
Guizhou	298	54	10.2	-0.2	596	-13	868	37
Hebei	75	58	2.3	0.2	928	4	333	47
Henan	138	18	8.4	0.5	879	-1	585	32
Heilongjiang	122	79	-8.1	0.7	755	0	428	74
Hubei	355	26	9.5	0.3	758	-4	998	29
Hunan	634	53	10.9	0.0	649	-8	1340	27
Jilin	145	89	-5.0	0.6	805	-1	502	70
Jiangsu	190	-10	8.6	0.3	849	-2	747	12
Jiangxi	770	39	11.8	-0.1	691	-10	1484	22
Liaoning	153	89	-0.9	0.5	869	2	550	72
Inner Mongolia	115	176	-6.6	0.2	833	0	395	97
Ningxia	44	37	1.2	-0.1	946	-2	207	23
Sichuan	129	22	8.7	-0.4	773	-6	509	22
Shandong	101	31	6.6	0.6	925	2	434	34
Shaanxi	110	40	4.8	0.0	841	-3	469	36
Shanxi	113	110	1.2	0.0	930	1	500	94
Yunnan	118	1	12.4	-1.1	964	-6	458	2
Zhejiang	545	21	10.0	0.0	742	-7	1285	18

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Annex A. Agroclimatic indicators and BIOMSS