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Exective Summary
Global agroclimatic patterns
Crop and environmental conditions in major production zones
Main producing and exporting countries
China
Focus and perspectives
Annex
Annex A. Agroclimatic indicators and BIOMSSAnnex
Authors: 超级管理员 | Edit: xingqiang
Table A.1. October 2016 - January 2017 agroclimatic indicators and biomass by global Monitoring and Reporting Unit
| 65 Global MRUs | RAIN Current(mm) | RAIN 15YA dep. (%) | TEMP Current (°C) | TEMP 15YA dep. (°C) | RADPAR Current(MJ/m2) | RADPAR 15YA dep. (%) | BIOMSS Current (gDM/m2) | BIOMSS 5YA dep. (%) | |
| 1 | Equatorial central Africa | 510 | -8 | 25.9 | 0.4 | 1225 | 8 | 1496 | -4 |
| 2 | East African highlands | 121 | -40 | 19.8 | 0.1 | 1317 | 7 | 467 | -30 |
| 3 | Gulf of Guinea | 251 | 7 | 27.1 | -0.2 | 1148 | 0 | 685 | 3 |
| 4 | Horn of Africa | 189 | -44 | 24.8 | -0.3 | 1360 | 6 | 619 | -37 |
| 5 | Madagascar (main) | 449 | -41 | 24.3 | -0.7 | 1381 | 8 | 1299 | -21 |
| 6 | Southwest Madagascar | 353 | -20 | 24.8 | -0.9 | 1478 | 3 | 1089 | -10 |
| 7 | North Africa-Mediterranean | 163 | -7 | 13.2 | -0.3 | 698 | -1 | 566 | -2 |
| 8 | Sahel | 41 | -19 | 28.0 | 0.2 | 1276 | 1 | 135 | -19 |
| 9 | Southern Africa | 474 | 7 | 24.9 | -0.6 | 1369 | 2 | 1308 | 3 |
| 10 | Western Cape (South Africa) | 44 | -65 | 18.6 | 0.0 | 1598 | 4 | 221 | -55 |
| 11 | British Columbia to Colorado | 330 | 32 | -3.8 | -0.2 | 444 | -4 | 509 | 11 |
| 12 | Northern Great Plains | 213 | 35 | 1.3 | 1.0 | 477 | -5 | 647 | 28 |
| 13 | Corn Belt | 371 | 1 | 3.7 | 1.5 | 431 | -5 | 885 | 11 |
| 14 | Cotton Belt to Mexican Nordeste | 344 | -8 | 13.5 | 1.4 | 667 | -2 | 957 | -1 |
| 15 | Sub-boreal America | 180 | 18 | -6.0 | 1.9 | 231 | -13 | 451 | 15 |
| 16 | West Coast (North America) | 425 | 20 | 6.7 | -0.4 | 496 | -8 | 825 | 15 |
| 17 | Sierra Madre | 104 | -18 | 15.6 | 0.4 | 1024 | 0 | 384 | -11 |
| 18 | SW U.S. and N. Mexican highlands | 145 | 51 | 9.0 | 0.8 | 753 | -4 | 459 | 22 |
| 19 | Northern South and Central America | 472 | 2 | 25.8 | -0.2 | 961 | 2 | 1139 | 3 |
| 20 | Caribbean | 328 | -2 | 24.4 | -0.7 | 903 | -2 | 798 | -14 |
| 21 | Central-northern Andes | 598 | 5 | 16.6 | 0.0 | 1172 | 4 | 1282 | 1 |
| 22 | Nordeste (Brazil) | 196 | -30 | 28.6 | 0.8 | 1378 | 1 | 550 | -28 |
| 23 | Central eastern Brazil | 720 | -4 | 26.2 | -0.6 | 1268 | 4 | 1801 | -2 |
| 24 | Amazon | 962 | 20 | 27.8 | -0.5 | 1098 | 1 | 2054 | 5 |
| 25 | Central-north Argentina | 453 | 4 | 25.1 | -1.3 | 1351 | 5 | 1366 | 3 |
| 26 | Pampas | 759 | 19 | 22.5 | -0.7 | 1379 | 1 | 1717 | 7 |
| 27 | Western Patagonia | 86 | -44 | 13.4 | 0.0 | 1410 | -2 | 377 | -28 |
| 28 | Semi-arid Southern Cone | 102 | -17 | 18.6 | -0.6 | 1543 | 4 | 412 | -5 |
| 29 | Caucasus | 266 | -6 | 2.1 | -1.6 | 554 | 1 | 684 | -11 |
| 30 | Pamir area | 246 | 77 | 2.8 | 0.3 | 709 | -2 | 517 | 24 |
| 31 | Western Asia | 156 | 17 | 6.5 | -0.5 | 653 | 0 | 453 | 1 |
| 32 | Gansu-Xinjiang (China) | 135 | 156 | -3.6 | 0.3 | 564 | -4 | 400 | 127 |
| 33 | Hainan (China) | 536 | 46 | 22.3 | 0.5 | 669 | -15 | 935 | 41 |
| 34 | Huanghuaihai (China) | 168 | 107 | 6.7 | 0.6 | 566 | -13 | 639 | 99 |
| 35 | Inner Mongolia (China) | 123 | 151 | -5.2 | 0.7 | 548 | -4 | 410 | 91 |
| 36 | Loess region (China) | 159 | 121 | 2.8 | 1.3 | 614 | -9 | 582 | 101 |
| 37 | Lower Yangtze (China) | 221 | -12 | 12.5 | 1.0 | 552 | -21 | 790 | 6 |
| 38 | Northeast China | 172 | 90 | -8.7 | -0.6 | 472 | -3 | 345 | 7 |
| 39 | Qinghai-Tibet (China) | 120 | 17 | 2.4 | 1.1 | 864 | 2 | 354 | 15 |
| 40 | Southern China | 170 | -7 | 17.4 | 1.0 | 726 | -9 | 577 | 4 |
| 41 | Southwest China | 149 | -5 | 10.3 | 0.9 | 529 | -12 | 527 | 0 |
| 42 | Taiwan (China) | 250 | 33 | 19.3 | 0.7 | 741 | -3 | 694 | 17 |
| 43 | East Asia | 174 | -18 | -1.4 | -0.2 | 499 | -4 | 515 | -5 |
| 44 | Southern Himalayas | 136 | -4 | 18.5 | 0.7 | 885 | 0 | 384 | -4 |
| 45 | Southern Asia | 122 | -48 | 23.8 | -0.2 | 1068 | 4 | 343 | -39 |
| 46 | Southern Japan and Korea | 303 | -25 | 9.6 | 0.5 | 573 | -4 | 1056 | -6 |
| 47 | Southern Mongolia | 140 | 366 | -9.9 | 0.3 | 462 | -4 | 340 | 168 |
| 48 | Punjab to Gujarat | 84 | 201 | 21.3 | -0.1 | 964 | 0 | 226 | 114 |
| 49 | Maritime Southeast Asia | 1285 | 15 | 25.5 | -0.5 | 928 | -5 | 2345 | 6 |
| 50 | Mainland Southeast Asia | 631 | 79 | 25.3 | 0.0 | 906 | -8 | 1138 | 44 |
| 51 | Eastern Siberia | 116 | -31 | -13.0 | -2.3 | 292 | 4 | 220 | -33 |
| 52 | Eastern Central Asia | 52 | -3 | -16.8 | -0.9 | 358 | 0 | 151 | -21 |
| 53 | Northern Australia | 676 | 13 | 26.9 | -0.7 | 1258 | -3 | 1506 | 5 |
| 54 | Queensland to Victoria | 195 | -21 | 20.5 | -0.4 | 1494 | 1 | 772 | -6 |
| 55 | Nullarbor to Darling | 61 | -40 | 18.8 | -1.0 | 1609 | 2 | 240 | -44 |
| 56 | New Zealand | 145 | -52 | 13.4 | -0.3 | 1274 | -2 | 667 | -36 |
| 57 | Boreal Eurasia | 258 | -2 | -4.2 | -0.7 | 130 | 0 | 455 | -13 |
| 58 | Ukraine to Ural mountains | 212 | 4 | -2.8 | -1.6 | 192 | -5 | 552 | -12 |
| 59 | Mediterranean Europe and Turkey | 244 | -24 | 7.9 | -1.4 | 542 | 1 | 796 | -16 |
| 60 | W. Europe (non Mediterranean) | 231 | -20 | 3.9 | -2.1 | 299 | -3 | 797 | -14 |
| 61 | Boreal America | 276 | -12 | -7.5 | 0.6 | 145 | -1 | 375 | 7 |
| 62 | Ural to Altai mountains | 175 | 32 | -9.8 | -1.9 | 241 | -7 | 314 | -20 |
| 63 | Australian desert | 135 | 45 | 20.9 | -1.1 | 1569 | -1 | 564 | 39 |
| 64 | Sahara to Afghan deserts | 59 | -5 | 17.8 | 0.0 | 975 | 1 | 187 | -6 |
| 65 | Sub-arctic America | 121 | 91 | -15.2 | 3.6 | 38 | 6 | 166 | 205 |
Table A.2. October 2016 - January 2017 agroclimatic indicators and biomass by country
| 31 Countries | RAIN Current (mm) | RAIN 15YA Departure (%) | TEMP Current (°C) | TEMP 15YA Departure (°C) | RADPAR Current (MJ/m2) | RADPAR 15YA Departure (%) | BIOMSS Current (gDM/m2) | BIOMSS 5YA Departure (%) | |
| [ARG] | Argentina | 608 | 23 | 22.1 | -0.9 | 1417 | 2 | 1466 | 8 |
| [AUS] | Australia | 216 | -15 | 20.9 | -0.5 | 1499 | 1 | 705 | -8 |
| [BGD] | Bangladesh | 240 | 5 | 22.4 | -0.2 | 922 | 0 | 613 | 16 |
| [BRA] | Brazil | 769 | 5 | 26.4 | -0.4 | 1233 | 2 | 1719 | -2 |
| [CAN] | Canada | 259 | 12 | -4.1 | 1.5 | 282 | -9 | 508 | 17 |
| [CHN] | China | 176 | 12 | 7.5 | 0.7 | 577 | -12 | 531 | 25 |
| [DEU] | Germany | 194 | -24 | 3.2 | -1.4 | 228 | -8 | 828 | -11 |
| [EGY] | Egypt | 37 | -35 | 17.5 | -0.6 | 798 | 0 | 153 | -3 |
| [ETH] | Ethiopia | 116 | -26 | 20.2 | 0.2 | 1310 | 8 | 446 | -20 |
| [FRA] | France | 201 | -36 | 5.6 | -3.5 | 357 | 3 | 683 | -35 |
| [GBR] | UK | 255 | -31 | 6.4 | -2.3 | 200 | -1 | 967 | -18 |
| [IDN] | Indonesia | 1251 | 13 | 25.6 | -0.6 | 946 | -5 | 2357 | 6 |
| [IND] | India | 101 | -30 | 21.9 | 0.1 | 1017 | 3 | 287 | -21 |
| [IRN] | Iran | 188 | -1 | 7.5 | -0.3 | 751 | 1 | 482 | -15 |
| [KAZ] | Kazakhstan | 170 | 41 | -7.3 | -1.3 | 301 | -8 | 394 | -7 |
| [KHM] | Cambodia | 784 | 120 | 27.1 | -0.3 | 934 | -10 | 1449 | 62 |
| [MEX] | Mexico | 148 | -24 | 19.7 | 0.6 | 969 | 1 | 449 | -8 |
| [MMR] | Myanmar | 248 | 7 | 22.7 | 0.2 | 913 | -3 | 713 | 10 |
| [NGA] | Nigeria | 170 | -5 | 27.2 | 0.0 | 1218 | 0 | 387 | -9 |
| [PAK] | Pakistan | 85 | 30 | 15.2 | 0.4 | 860 | -1 | 213 | 20 |
| [PHL] | Philippines | 1354 | 50 | 25.3 | -0.5 | 858 | -6 | 2099 | 20 |
| [POL] | Poland | 250 | 31 | 1.9 | -1.0 | 197 | -14 | 794 | -2 |
| [ROU] | Romania | 242 | 11 | 0.9 | -2.2 | 347 | -6 | 733 | -2 |
| [RUS] | Russia | 176 | -1 | -7.2 | -1.8 | 221 | -2 | 380 | -18 |
| [THA] | Thailand | 581 | 82 | 25.4 | 0.0 | 930 | -7 | 1006 | 38 |
| [TUR] | Turkey | 272 | -15 | 3.9 | -1.3 | 594 | 2 | 745 | -16 |
| [UKR] | Ukraine | 249 | 33 | 0.2 | -1.7 | 260 | -7 | 695 | -4 |
| [USA] | USA | 317 | 5 | 6.7 | 1.1 | 554 | -3 | 781 | 12 |
| [UZB] | Uzbekistan | 300 | 100 | 3.9 | -0.8 | 551 | -2 | 725 | 51 |
| [VNM] | Vietnam | 750 | 74 | 22.7 | 0.7 | 723 | -11 | 1218 | 38 |
| [ZAF] | South Africa | 402 | 9 | 20.9 | -0.2 | 1416 | 1 | 1179 | -1 |
Table A.3. Argentina, October 2016 - January 2017 agroclimatic indicators and biomass (by province)
| RAIN Current (mm) | RAIN 15YA Departure (%) | TEMP Current (°C) | TEMP 15YA Departure (°C) | RADPAR Current (MJ/m2) | RADPAR 15YA Departure (%) | BIOMSS Current (gDM/m2) | BIOMSS 5YA Departure (%) | |
| Buenos Aires | 474 | 7 | 20.0 | -0.4 | 1488 | 0 | 1336 | 0 |
| Chaco | 764 | 37 | 24.8 | -1.5 | 1360 | 1 | 1904 | 25 |
| Cordoba | 456 | 3 | 21.8 | -1.1 | 1461 | 3 | 1351 | -4 |
| Corrientes | 1072 | 42 | 23.9 | -1.2 | 1365 | 0 | 2039 | 18 |
| Entre Rios | 849 | 47 | 22.3 | -1.0 | 1420 | 0 | 1790 | 14 |
| La Pampa | 460 | 18 | 21.0 | -0.5 | 1572 | 3 | 1433 | 15 |
| Misiones | 939 | 4 | 23.8 | -0.8 | 1342 | 4 | 2098 | 8 |
| Santiago Del Estero | 480 | 9 | 24.7 | -1.4 | 1345 | 2 | 1472 | 9 |
| San Luis | 389 | -4 | 21.0 | -1.0 | 1547 | 6 | 1360 | 2 |
| Salta | 482 | 6 | 24.1 | -1.2 | 1301 | 7 | 1350 | 2 |
| Santa Fe | 817 | 48 | 23.0 | -1.1 | 1412 | 0 | 1859 | 18 |
| Tucuman | 352 | -18 | 23.1 | -1.2 | 1322 | 8 | 1136 | -13 |
Table A.4. Australia, October 2016 - January 2017 agroclimatic indicators and biomass (by state)
| RAIN Current (mm) | RAIN 15YA Departure (%) | TEMP Current (°C) | TEMP 15YA Departure (°C) | RADPAR Current (MJ/m2) | RADPAR 15YA Departure (%) | BIOMSS Current (gDM/m2) | BIOMSS 5YA Departure (%) | |
| New South Wales | 196 | -19 | 21.3 | -0.3 | 1527 | 2 | 776 | -4 |
| South Australia | 136 | 23 | 18.3 | -0.9 | 1491 | -2 | 641 | 28 |
| Victoria | 148 | -25 | 17.0 | -0.8 | 1435 | -2 | 704 | -8 |
| W. Australia | 110 | -10 | 19.6 | -0.9 | 1594 | 2 | 284 | -36 |
Table A.5. Brazil, October 2016 - January 2017 agroclimatic indicators and biomass (by state)
| RAIN Current (mm) | RAIN 15YA Departure (%) | TEMP Current (°C) | TEMP 15YA Departure (°C) | RADPAR Current (MJ/m2) | RADPAR 15YA Departure (%) | BIOMSS Current (gDM/m2) | BIOMSS 5YA Departure (%) | |
| Ceara | 166 | -11 | 28.8 | 0.2 | 1369 | -2 | 513 | 0 |
| Goias | 737 | -14 | 25.7 | -0.7 | 1315 | 8 | 2022 | -4 |
| Mato Grosso Do Sul | 740 | 6 | 26.2 | -1.5 | 1306 | 3 | 1961 | 4 |
| Mato Grosso | 1057 | 6 | 27.3 | -0.5 | 1184 | 3 | 2347 | 2 |
| Minas Gerais | 719 | -12 | 24.8 | 0.1 | 1299 | 5 | 1738 | -8 |
| Parana | 719 | -8 | 23.1 | -0.7 | 1267 | 4 | 1917 | 0 |
| Rio Grande Do Sul | 977 | 30 | 22.7 | -0.4 | 1316 | 0 | 1858 | 7 |
| Santa Catarina | 846 | 2 | 21.2 | -0.1 | 1187 | -1 | 1811 | -8 |
| Sao Paulo | 821 | 4 | 24.3 | -0.7 | 1272 | 4 | 2062 | 5 |
Table A.6. Canada, October 2016 - January 2017 agroclimatic indicators and biomass (by province)
| RAIN Current (mm) | RAIN 15YA Departure (%) | TEMP Current (°C) | TEMP 15YA Departure (°C) | RADPAR Current (MJ/m2) | RADPAR 15YA Departure (%) | BIOMSS Current (gDM/m2) | BIOMSS 5YA Departure (%) | |
| Alberta | 101 | -5 | -5.8 | 0.9 | 255 | -9 | 407 | 3 |
| Manitoba | 198 | 63 | -4.7 | 2.6 | 276 | -13 | 541 | 29 |
| Saskatchewan | 149 | 50 | -5.9 | 1.7 | 271 | -13 | 457 | 18 |
Table A.7. India, October 2016 - January 2017 agroclimatic indicators and biomass (by state)
| RAIN Current (mm) | RAIN 15YA Departure (%) | TEMP Current (°C) | TEMP 15YA Departure (°C) | RADPAR Current (MJ/m2) | RADPAR 15YA Departure (%) | BIOMSS Current (gDM/m2) | BIOMSS 5YA Departure (%) | |
| Arunachal Pradesh | 217 | 1 | 16.4 | 1.3 | 812 | 1 | 684 | 1 |
| Andhra Pradesh | 67 | -71 | 25.0 | -0.4 | 1104 | 6 | 221 | -60 |
| Assam | 168 | -7 | 22.8 | 1.2 | 851 | 1 | 506 | 0 |
| Bihar | 66 | -23 | 21.4 | -0.2 | 936 | 1 | 203 | -27 |
| Chhattisgarh | 79 | -25 | 21.8 | -0.4 | 1062 | 3 | 223 | -37 |
| Daman and Diu | 84 | 84 | 24.5 | -1.4 | 1083 | 0 | 239 | 42 |
| Delhi | 127 | 240 | 19.9 | 0.5 | 918 | 1 | 425 | 148 |
| Gujarat | 142 | 473 | 24.3 | -0.2 | 1052 | -1 | 344 | 264 |
| Goa | 63 | -69 | 24.5 | -0.4 | 1160 | 3 | 293 | -46 |
| Himachal Pradesh | 218 | 84 | 4.4 | 1.3 | 857 | -2 | 415 | 13 |
| Haryana | 125 | 201 | 18.9 | 0.4 | 902 | 0 | 376 | 125 |
| Jharkhand | 48 | -58 | 21.0 | 0.2 | 998 | 2 | 181 | -51 |
| Kerala | 205 | -62 | 25.4 | -0.2 | 1097 | 2 | 695 | -40 |
| Karnataka | 53 | -74 | 24.1 | -0.2 | 1159 | 5 | 203 | -64 |
| Meghalaya | 184 | -28 | 19.4 | 1.5 | 875 | 0 | 509 | 4 |
| Maharashtra | 59 | -42 | 23.4 | -0.5 | 1095 | 3 | 192 | -39 |
| Manipur | 206 | 8 | 17.3 | 1.2 | 891 | 1 | 579 | -1 |
| Madhya Pradesh | 39 | -34 | 21.4 | 0.0 | 1037 | 3 | 166 | -24 |
| Mizoram | 303 | 17 | 18.5 | 0.2 | 935 | 0 | 716 | 6 |
| Nagaland | 148 | -15 | 17.4 | 1.9 | 841 | 1 | 466 | -20 |
| Orissa | 126 | -28 | 23.1 | 0.0 | 1042 | 4 | 324 | -33 |
| Puducherry | 260 | -82 | 27.0 | -0.1 | 1059 | 9 | 957 | 0 |
| Punjab | 107 | 73 | 17.8 | 0.6 | 849 | 0 | 300 | 23 |
| Rajasthan | 66 | 292 | 21.0 | -0.3 | 981 | 0 | 205 | 192 |
| Sikkim | 56 | -62 | 6.1 | 1.2 | 908 | 3 | 208 | -45 |
| Tamil Nadu | 216 | -60 | 26.6 | 0.1 | 1084 | 9 | 748 | -34 |
| Tripura | 396 | 60 | 22.1 | 0.2 | 912 | -1 | 789 | 31 |
| Uttarakhand | 153 | 41 | 11.0 | 3.1 | 898 | 0 | 399 | 22 |
| Uttar Pradesh | 86 | 31 | 20.4 | 0.3 | 946 | 1 | 263 | 12 |
| West Bengal | 146 | -18 | 23.0 | 0.5 | 948 | 2 | 380 | -17 |
Table A.8. Kazakhstan, October 2016 - January 2017 agroclimatic indicators and biomass (by oblast)
| RAIN Current (mm) | RAIN 15YA Departure (%) | TEMP Current (°C) | TEMP 15YA Departure (°C) | RADPAR Current (MJ/m2) | RADPAR 15YA Departure (%) | BIOMSS Current (gDM/m2) | BIOMSS 5YA Departure (%) | |
| Akmolinskaya | 139 | 33 | -9.0 | -1.1 | 235 | -12 | 325 | -18 |
| Karagandinskaya | 146 | 50 | -8.8 | -1.1 | 295 | -11 | 320 | -20 |
| Kustanayskaya | 135 | 22 | -8.8 | -1.9 | 233 | -8 | 349 | -17 |
| Pavlodarskaya | 129 | 58 | -9.1 | -1.3 | 234 | -12 | 316 | -15 |
| Severo kazachstanskaya | 143 | 33 | -9.9 | -1.9 | 200 | -9 | 306 | -22 |
| Vostochno kazachstanskaya | 219 | 45 | -10.0 | -1.0 | 330 | -11 | 308 | -16 |
| Zapadno kazachstanskaya | 128 | -2 | -4.8 | -2.0 | 272 | -3 | 502 | -8 |
Table A.9. Russia, October 2016 - January 2017 agroclimatic indicators and biomass (by oblast, kray and republic)
| RAIN Current (mm) | RAIN 15YA Departure (%) | TEMP Current (°C) | TEMP 15YA Departure (°C) | RADPAR Current (MJ/m2) | RADPAR 15YA Departure (%) | BIOMSS Current (gDM/m2) | BIOMSS 5YA Departure (%) | |
| Bashkortostan Rep. | 220 | 17 | -8.4 | -2.3 | 192 | -4 | 352 | -22 |
| Chelyabinskaya Oblast | 137 | 17 | -9.3 | -2.4 | 203 | -6 | 328 | -19 |
| Gorodovikovsk | 254 | 3 | 1.4 | -2.2 | 323 | -1 | 778 | -7 |
| Krasnodarskiy Kray | 181 | -23 | -4.8 | -1.5 | 286 | 1 | 432 | -19 |
| Kurganskaya Oblast | 127 | 7 | -10.7 | -3.2 | 189 | -2 | 298 | -26 |
| Kirovskaya Oblast | 169 | -27 | -8.4 | -3.0 | 134 | 4 | 354 | -25 |
| Kurskaya Oblast | 221 | 18 | -2.0 | -1.5 | 214 | -5 | 585 | -14 |
| Lipetskaya Oblast | 205 | 8 | -2.9 | -1.6 | 206 | -4 | 545 | -16 |
| Mordoviya Rep. | 162 | -21 | -4.6 | -1.6 | 184 | 1 | 480 | -16 |
| Novosibirskaya Oblast | 180 | 24 | -11.8 | -2.1 | 192 | -2 | 247 | -33 |
| Nizhegorodskaya O. | 169 | -22 | -5.2 | -1.9 | 155 | 2 | 458 | -18 |
| Orenburgskaya Oblast | 179 | 15 | -7.0 | -1.8 | 230 | -7 | 408 | -16 |
| Omskaya Oblast | 148 | 14 | -12.1 | -2.8 | 183 | 0 | 255 | -32 |
| Permskaya Oblast | 187 | -13 | -10.5 | -3.4 | 146 | 5 | 297 | -29 |
| Penzenskaya Oblast | 168 | -17 | -4.5 | -1.6 | 199 | -2 | 488 | -15 |
| Rostovskaya Oblast | 159 | -29 | 0.1 | -1.7 | 303 | 0 | 656 | -12 |
| Ryazanskaya Oblast | 178 | -11 | -3.6 | -1.5 | 177 | -1 | 515 | -16 |
| Stavropolskiy Kray | 208 | 5 | 1.7 | -2.2 | 337 | -5 | 731 | -4 |
| Sverdlovskaya Oblast | 139 | -2 | -11.5 | -3.8 | 156 | -1 | 280 | -30 |
| Samarskaya Oblast | 187 | 9 | -6.1 | -2.1 | 213 | -1 | 438 | -17 |
| Saratovskaya Oblast | 138 | -16 | -4.1 | -1.7 | 242 | -1 | 518 | -12 |
| Tambovskaya Oblast | 190 | -5 | -3.4 | -1.5 | 207 | -3 | 530 | -15 |
| Tyumenskaya Oblast | 143 | 10 | -12.2 | -3.5 | 168 | -2 | 265 | -31 |
| Tatarstan Rep. | 176 | -9 | -6.8 | -2.5 | 180 | 1 | 404 | -23 |
| Ulyanovskaya Oblast | 163 | -8 | -5.4 | -1.9 | 198 | -1 | 456 | -17 |
| Udmurtiya Rep. | 180 | -16 | -8.8 | -3.1 | 151 | 4 | 341 | -27 |
| Volgogradskaya O. | 153 | -11 | -2.0 | -1.8 | 271 | -1 | 607 | -8 |
| Voronezhskaya Oblast | 192 | 3 | -2.1 | -1.4 | 233 | -3 | 592 | -11 |
Table A.10. United States, October 2016 - January 2017 agroclimatic indicators and biomass (by state)
| RAIN Current (mm) | RAIN 15YA Departure (%) | TEMP Current (°C) | TEMP 15YA Departure (°C) | RADPAR Current (MJ/m2) | RADPAR 15YA Departure (%) | BIOMSS Current (gDM/m2) | BIOMSS 5YA Departure (%) | |
| Arkansas | 416 | -20 | 11.5 | 1.6 | 604 | -3 | 1261 | 2 |
| California | 348 | 45 | 7.9 | -0.2 | 600 | -8 | 757 | 26 |
| Idaho | 367 | 75 | -2.9 | -1.1 | 454 | -7 | 601 | 11 |
| Indiana | 360 | -8 | 6.1 | 1.4 | 484 | -5 | 1075 | 8 |
| Illinois | 318 | -10 | 5.8 | 1.5 | 490 | -6 | 1024 | 7 |
| Iowa | 299 | 36 | 3.0 | 1.6 | 473 | -8 | 921 | 32 |
| Kansas | 189 | 11 | 6.3 | 1.0 | 616 | -2 | 538 | -11 |
| Michigan | 364 | 16 | 2.8 | 1.6 | 365 | -9 | 890 | 16 |
| Minnesota | 293 | 63 | -1.0 | 1.7 | 395 | -5 | 718 | 35 |
| Missouri | 304 | -14 | 7.5 | 1.4 | 535 | -6 | 985 | 0 |
| Montana | 268 | 115 | -2.8 | -0.9 | 427 | -4 | 620 | 43 |
| Nebraska | 186 | 38 | 3.0 | 1.1 | 555 | -3 | 724 | 44 |
| North Dakota | 250 | 113 | -2.8 | 1.0 | 398 | -5 | 642 | 57 |
| Ohio | 346 | 0 | 5.9 | 1.5 | 465 | -4 | 1074 | 10 |
| Oklahoma | 248 | -7 | 10.1 | 1.0 | 655 | -2 | 828 | 1 |
| Oregon | 429 | 22 | 2.4 | -1.1 | 397 | -10 | 811 | 9 |
| South Dakota | 241 | 86 | 0.4 | 0.7 | 488 | -2 | 775 | 75 |
| Texas | 271 | 2 | 14.7 | 1.4 | 704 | -4 | 754 | 7 |
| Washington | 407 | 13 | 1.5 | -0.9 | 335 | -8 | 797 | 11 |
| Wisconsin | 353 | 35 | 0.9 | 1.5 | 402 | -5 | 805 | 19 |
Table A.11. China, October 2016 - January 2017 agroclimatic indicators and biomass (by province)
| RAIN Current (mm) | RAIN 15YA Departure (%) | TEMP Current (°C) | TEMP 15YA Departure (°C) | RADPAR Current (MJ/m2) | RADPAR 15YA Departure (%) | BIOMSS Current (gDM/m2) | BIOMSS 5YA Departure (%) | |
| Anhui | 245 | 15 | 10.2 | 0.6 | 524 | -23 | 915 | 32 |
| Chongqing | 176 | 1 | 9.9 | 0.7 | 396 | -22 | 567 | -8 |
| Fujian | 286 | 19 | 15.0 | 1.7 | 604 | -20 | 832 | 22 |
| Gansu | 122 | 110 | 1.6 | 1.3 | 650 | -6 | 462 | 115 |
| Guangdong | 221 | 25 | 18.0 | 1.0 | 706 | -14 | 707 | 41 |
| Guangxi | 141 | -36 | 17.0 | 1.2 | 644 | -11 | 500 | -19 |
| Guizhou | 141 | -25 | 11.3 | 1.2 | 460 | -16 | 503 | -16 |
| Hebei | 90 | 83 | 1.0 | 0.6 | 578 | -6 | 401 | 83 |
| Heilongjiang | 189 | 110 | -11.4 | -1.3 | 443 | -1 | 290 | -6 |
| Henan | 206 | 91 | 8.0 | 0.6 | 551 | -18 | 785 | 79 |
| Hubei | 222 | 22 | 9.5 | 0.5 | 502 | -22 | 774 | 17 |
| Hunan | 177 | -32 | 11.6 | 0.5 | 501 | -24 | 670 | -16 |
| Jiangsu | 285 | 85 | 9.8 | 0.7 | 523 | -22 | 1005 | 82 |
| Jiangxi | 224 | -26 | 13.4 | 1.2 | 562 | -22 | 791 | -5 |
| Jilin | 192 | 104 | -6.8 | -0.1 | 494 | -5 | 421 | 20 |
| Liaoning | 140 | 47 | -1.6 | 0.5 | 543 | -5 | 543 | 42 |
| Inner Mongolia | 121 | 147 | -8.3 | 0.2 | 508 | -3 | 335 | 65 |
| Ningxia | 122 | 182 | 1.1 | 1.8 | 671 | -3 | 457 | 171 |
| Shaanxi | 207 | 102 | 4.5 | 1.2 | 541 | -15 | 730 | 91 |
| Shandong | 162 | 114 | 6.7 | 0.8 | 575 | -11 | 658 | 115 |
| Shanxi | 117 | 85 | 0.9 | 1.6 | 605 | -8 | 485 | 77 |
| Sichuan | 102 | -1 | 9.0 | 0.9 | 563 | -7 | 387 | -1 |
| Yunnan | 134 | -20 | 12.9 | 0.8 | 772 | 0 | 472 | -11 |
| Zhejiang | 222 | -26 | 12.5 | 1.6 | 525 | -22 | 835 | -2 |