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Authors: 超级管理员 | Edit: Changsheng
Annex A. Agroclimatic indicators and BIOMSS
Table A.1. April-July 2018agroclimatic indicators and biomass by global Monitoring and Reporting Unit.All values are averages (TEMP) or totals (RAIN, RADPAR, BIOMSS) over thereporting period
|
| 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. (%) |
| C01 | Equatorial central Africa | 364 | -3 | 24.7 | -0.1 | 1056 | -2 | 1109 | 1 |
| C02 | East African highlands | 518 | -2 | 20.3 | -0.6 | 1135 | -2 | 1449 | 0 |
| C03 | Gulf of Guinea | 660 | 4 | 27.5 | -0.8 | 1011 | -7 | 1750 | 2 |
| C04 | Horn of Africa | 279 | 51 | 22.8 | -1.2 | 1104 | -3 | 756 | 26 |
| C05 | Madagascar (main) | 258 | 29 | 21.9 | -0.5 | 904 | -2 | 756 | 26 |
| C06 | Southwest Madagascar | 67 | -4 | 21.6 | -0.5 | 965 | 0 | 270 | -1 |
| C07 | North Africa-Mediterranean | 121 | 30 | 20.2 | -1.5 | 1405 | -7 | 442 | 23 |
| C08 | Sahel | 424 | 21 | 31.2 | -0.8 | 1277 | -6 | 1183 | 15 |
| C09 | Southern Africa | 127 | 36 | 19.8 | -0.2 | 952 | -2 | 332 | 9 |
| C10 | Western Cape (South Africa) | 73 | -53 | 13.7 | 0.8 | 681 | 0 | 325 | -44 |
| C11 | British Columbia to Colorado | 221 | 6 | 11 | 0.5 | 1352 | -5 | 850 | 4 |
| C12 | Northern Great Plains | 421 | 13 | 16.7 | -0.2 | 1319 | -1 | 1276 | 8 |
| C13 | Corn Belt | 389 | -11 | 16.2 | -0.4 | 1225 | 0 | 1269 | -9 |
| C14 | Cotton Belt to Mexican Nordeste | 439 | -5 | 23.3 | -0.4 | 1288 | -2 | 1326 | -2 |
| C15 | Sub-boreal America | 257 | -13 | 10.7 | -0.2 | 1190 | 0 | 1032 | -9 |
| C16 | West Coast (North America) | 92 | -23 | 15.6 | 0.3 | 1456 | -2 | 337 | -20 |
| C17 | Sierra Madre | 347 | -12 | 21.1 | -0.2 | 1414 | -2 | 1021 | -3 |
| C18 | SW U.S. and N. Mexican highlands | 129 | 3 | 21.5 | 0.7 | 1528 | -3 | 495 | 2 |
| C19 | Northern South and Central America | 764 | -2 | 26.9 | -0.8 | 1120 | 0 | 1641 | -5 |
| C20 | Caribbean | 744 | 7 | 26.2 | -0.8 | 1251 | -5 | 1593 | -7 |
| C21 | Central-northern Andes | 362 | -8 | 14.8 | -0.3 | 987 | 1 | 837 | 1 |
| C22 | Nordeste (Brazil) | 164 | -22 | 26.2 | 0 | 1010 | 0 | 496 | -22 |
| C23 | Central eastern Brazil | 177 | -29 | 23.6 | -0.5 | 971 | 4 | 545 | -28 |
| C24 | Amazon | 659 | 3 | 26.7 | -0.9 | 966 | 1 | 1451 | -3 |
| C25 | Central-north Argentina | 199 | 71 | 16.9 | -0.6 | 701 | 0 | 478 | 28 |
| C26 | Pampas | 433 | 5 | 16.2 | 0.3 | 642 | -4 | 1068 | 3 |
| C27 | Western Patagonia | 328 | -27 | 5.8 | -1.1 | 461 | -4 | 894 | -2 |
| C28 | Semi-arid Southern Cone | 99 | 38 | 9.4 | -0.3 | 656 | -2 | 340 | 18 |
| C29 | Caucasus | 197 | -14 | 17.7 | 0.6 | 1353 | 0 | 761 | -12 |
| C30 | Pamir area | 229 | 7 | 17.4 | -0.5 | 1422 | -4 | 700 | -2 |
| C31 | Western Asia | 98 | 7 | 23 | -0.5 | 1423 | -3 | 377 | 3 |
| C32 | Gansu-Xinjiang (China) | 217 | 43 | 17.6 | -0.4 | 1272 | -9 | 730 | 36 |
| C33 | Hainan (China) | 1121 | 53 | 26.8 | -1.3 | 1102 | -6 | 2003 | 17 |
| C34 | Huanghuaihai (China) | 442 | 10 | 23 | 0.4 | 1067 | -15 | 1277 | 7 |
| C35 | Inner Mongolia (China) | 343 | 24 | 17.2 | 0.8 | 1178 | -8 | 1129 | 13 |
| C36 | Loess region (China) | 330 | 16 | 18.5 | 0 | 1101 | -14 | 1162 | 11 |
| C37 | Lower Yangtze (China) | 859 | -2 | 23.9 | 0.1 | 1015 | -5 | 1923 | 1 |
| C38 | Northeast China | 327 | -7 | 16.6 | 0.4 | 1097 | -7 | 1187 | 1 |
| C39 | Qinghai-Tibet (China) | 770 | 8 | 11.7 | 0.1 | 1169 | -2 | 1263 | 5 |
| C40 | Southern China | 837 | -6 | 23.9 | -0.5 | 1007 | -2 | 1913 | 0 |
| C41 | Southwest China | 638 | 3 | 20.8 | 0 | 985 | -4 | 1667 | 2 |
| C42 | Taiwan (China) | 682 | -28 | 24.4 | -0.1 | 1140 | 1 | 1465 | -15 |
| C43 | East Asia | 356 | -24 | 15.5 | 0.1 | 1082 | -5 | 1135 | -13 |
| C44 | Southern Himalayas | 997 | 14 | 26.4 | -0.6 | 1084 | -5 | 1658 | 5 |
| C45 | Southern Asia | 827 | 21 | 29.5 | -0.6 | 1111 | -3 | 1533 | 13 |
| C46 | Southern Japan and Korea | 682 | -8 | 20 | 0.6 | 1100 | 0 | 1577 | -9 |
| C47 | Southern Mongolia | 364 | 84 | 16.3 | -0.2 | 1411 | -2 | 933 | 37 |
| C48 | Punjab to Gujarat | 446 | 26 | 32.2 | -0.3 | 1253 | -7 | 875 | 13 |
| C49 | Maritime Southeast Asia | 868 | -8 | 25.8 | -0.5 | 972 | -2 | 1921 | -7 |
| C50 | Mainland Southeast Asia | 1054 | 15 | 27.7 | -1.1 | 1029 | -5 | 1997 | 2 |
| C51 | Eastern Siberia | 198 | -17 | 9.4 | -0.4 | 1067 | -7 | 890 | -11 |
| C52 | Eastern Central Asia | 292 | 26 | 11.1 | 0.2 | 1140 | -8 | 1050 | 10 |
| C53 | Northern Australia | 116 | -52 | 24.2 | -0.4 | 1024 | 3 | 403 | -38 |
| C54 | Queensland to Victoria | 83 | -51 | 12.9 | 0.3 | 704 | 4 | 366 | -42 |
| C55 | Nullarbor to Darling | 164 | -23 | 14 | 0.1 | 667 | 0 | 586 | -20 |
| C56 | New Zealand | 189 | -38 | 9.2 | 0 | 451 | -4 | 727 | -22 |
| C57 | Boreal Eurasia | 225 | -22 | 11.1 | 1.9 | 1115 | 5 | 920 | -14 |
| C58 | Ukraine to Ural mountains | 237 | -4 | 15.6 | 0.4 | 1169 | 4 | 975 | -5 |
| C59 | Mediterranean Europe and Turkey | 202 | 23 | 18 | 1 | 1345 | -5 | 745 | 13 |
| C60 | W. Europe (non Mediterranean) | 275 | -5 | 16.5 | 1.4 | 1192 | 3 | 1034 | -7 |
| C61 | Boreal America | 365 | 27 | 6.6 | 0.2 | 966 | -7 | 1020 | 3 |
| C62 | Ural to Altai mountains | 239 | 11 | 12.6 | -1.8 | 1139 | -6 | 988 | 10 |
| C63 | Australian desert | 73 | -24 | 14.5 | 0.2 | 742 | 5 | 342 | -20 |
| C64 | Sahara to Afghan deserts | 75 | 63 | 29.1 | -0.6 | 1478 | -4 | 269 | 42 |
| C65 | Sub-arctic America | 156 | 62 | -6.2 | -0.3 | 537 | -3 | 568 | 113 |
| AFG | Afghanistan | 55 | -30 | 20.2 | -0.5 | 1529 | -3 | 184 | -32 |
| AGO | Angola | 147 | 20 | 22.9 | 1.7 | 1087 | -3 | 413 | 24 |
| ARG | Argentina | 396 | 79 | 14.4 | -0.1 | 610 | -7 | 829 | 33 |
| AUS | Australia | 94 | -45 | 14 | 0.2 | 728 | 3 | 399 | -36 |
| BGD | Bangladesh | 1781 | 23 | 28.2 | -1.4 | 947 | -7 | 2444 | 13 |
| BLR | Belarus | 288 | 5 | 16.4 | 1.4 | 1129 | 4 | 1108 | -4 |
| BRA | Brazil | 308 | -16 | 24.1 | -0.4 | 958 | 2 | 776 | -18 |
| CAN | Canada | 245 | -18 | 11 | -0.1 | 1214 | 1 | 978 | -10 |
| CHN | China | 633 | 1 | 21 | 0.1 | 1049 | -6 | 1423 | 5 |
| DEU | Germany | 194 | -33 | 16.9 | 1.8 | 1198 | 9 | 834 | -28 |
| EGY | Egypt | 11 | 49 | 24.7 | 0.5 | 1553 | -3 | 57 | 47 |
| ETH | Ethiopia | 532 | -9 | 21.5 | -0.4 | 1162 | 0 | 1521 | -2 |
| FRA | France | 266 | -1 | 16.3 | 1.7 | 1205 | 0 | 1007 | -3 |
| GBR | United Kingdom | 251 | -15 | 13.1 | 1.6 | 1053 | 4 | 1006 | -13 |
| HUN | Hungary | 343 | 21 | 19.4 | 1.3 | 1235 | 3 | 1234 | 12 |
| IDN | Indonesia | 858 | -10 | 25.7 | -0.6 | 949 | -2 | 1851 | -8 |
| IND | India | 808 | 17 | 29.7 | -0.4 | 1146 | -4 | 1377 | 10 |
| IRN | Iran | 75 | -10 | 21.7 | -0.4 | 1424 | -5 | 300 | -2 |
| ITA | Italy | 287 | 16 | 19.4 | 0.5 | 1269 | -4 | 999 | 11 |
| KAZ | Kazakhstan | 193 | 10 | 14.7 | -1.6 | 1229 | -3 | 804 | 8 |
| KEN | Kenya | 508 | 48 | 20.8 | -1.2 | 1055 | -5 | 1194 | 20 |
| KHM | Cambodia | 857 | -1 | 28.4 | -1.4 | 1053 | -6 | 2064 | -1 |
| LKA | Sri_Lanka | 704 | 45 | 27.7 | -0.9 | 1099 | -4 | 1403 | 18 |
| MAR | Morocco | 91 | 22 | 18.2 | -2.3 | 1417 | -8 | 329 | 11 |
| MEX | Mexico | 401 | -9 | 24.6 | -0.4 | 1372 | -2 | 989 | -3 |
| MMR | Myanmar | 1221 | 20 | 26.6 | -0.8 | 981 | -5 | 1973 | 5 |
| MNG | Mongolia | 307 | 40 | 11.3 | 0.5 | 1231 | -5 | 1089 | 18 |
| MOZ | Mozambique | 164 | 61 | 22.9 | -0.6 | 926 | -2 | 448 | 31 |
| NGA | Nigeria | 678 | 10 | 28.5 | -0.8 | 1066 | -8 | 1691 | 6 |
| PAK | Pakistan | 240 | 5 | 27.9 | -0.6 | 1352 | -7 | 593 | 2 |
| PHL | Philippines | 871 | -5 | 26.7 | -0.5 | 1123 | -2 | 1901 | -3 |
| POL | Poland | 238 | -12 | 16.8 | 1.8 | 1172 | 8 | 928 | -17 |
| ROU | Romania | 369 | 14 | 17.7 | 0.9 | 1231 | 1 | 1253 | 5 |
| RUS | Russia | 241 | -1 | 13.9 | -0.4 | 1143 | -1 | 1002 | -1 |
| THA | Thailand | 839 | 11 | 27.6 | -1.2 | 1050 | -5 | 1990 | 4 |
| TUR | Turkey | 257 | 37 | 18.2 | 1 | 1402 | -1 | 892 | 17 |
| UKR | Ukraine | 246 | 0 | 18.2 | 1.1 | 1240 | 6 | 946 | -6 |
| USA | United States | 396 | 1 | 19 | -0.2 | 1301 | -2 | 1151 | 2 |
| UZB | Uzbekistan | 115 | 5 | 21.8 | -0.5 | 1414 | -2 | 425 | 2 |
| VNM | Vietnam | 926 | 11 | 26.5 | -0.8 | 1024 | -6 | 1967 | 1 |
| ZAF | South Africa | 69 | -19 | 14 | 0.1 | 834 | -1 | 298 | -15 |
| ZMB | Zambia | 76 | 23 | 21 | -0.4 | 1060 | -3 | 256 | 17 |
| Buenos Aires | 397 | 81 | 11.9 | 0.3 | 503 | -14 | 1070 | 46 |
| Chaco | 493 | 90 | 18.1 | -0.1 | 720 | 4 | 809 | 8 |
| Cordoba | 232 | 92 | 13.3 | -0.3 | 583 | -13 | 647 | 48 |
| Corrientes | 529 | 24 | 17.5 | -0.1 | 672 | -2 | 1208 | 6 |
| Entre Rios | 637 | 93 | 15.1 | 0.1 | 575 | -11 | 1265 | 37 |
| La Pampa | 216 | 62 | 11.6 | 0.1 | 518 | -15 | 687 | 43 |
| Misiones | 315 | -54 | 18.6 | 0.4 | 727 | 2 | 1034 | -35 |
| Santiago Del Estero | 376 | 281 | 16.5 | -0.3 | 671 | -3 | 588 | 65 |
| San Luis | 166 | 57 | 11.4 | -0.5 | 597 | -11 | 512 | 28 |
| Salta | 211 | 201 | 16.4 | -0.5 | 779 | 4 | 484 | 103 |
| Santa Fe | 684 | 193 | 15.7 | 0.1 | 611 | -8 | 988 | 39 |
| Tucuman | 59 | -13 | 14.7 | -0.4 | 751 | 2 | 242 | 1 |
| New South Wales | 73 | -56 | 12.7 | 0.5 | 736 | 6 | 311 | -48 |
| South Australia | 113 | -33 | 13 | 0.2 | 613 | 3 | 472 | -28 |
| Victoria | 120 | -41 | 11 | 0.1 | 545 | 0 | 509 | -32 |
| W. Australia | 154 | -24 | 14.8 | 0.1 | 702 | 1 | 561 | -20 |
| Ceara | 317 | -2 | 27.3 | -0.2 | 1072 | -1 | 882 | -9 |
| Goias | 169 | 8 | 23.4 | -0.9 | 1065 | 4 | 520 | 0 |
| Mato Grosso Do Sul | 150 | -53 | 23.4 | -0.2 | 936 | 5 | 516 | -48 |
| Mato Grosso | 209 | -4 | 25.7 | -1.1 | 1055 | 4 | 638 | -10 |
| Minas Gerais | 96 | -30 | 21.8 | -0.2 | 942 | 1 | 365 | -26 |
| Parana | 171 | -70 | 20.1 | 1.1 | 823 | 6 | 601 | -58 |
| Rio Grande Do Sul | 534 | -8 | 16.9 | 0.5 | 644 | -4 | 1519 | 1 |
| Santa Catarina | 285 | -51 | 17 | 0.7 | 721 | 4 | 954 | -35 |
| Sao Paulo | 85 | -71 | 21.7 | 0.6 | 906 | 5 | 369 | -61 |
Table A.6. Canada,April-July 2018 agroclimatic indicators and biomass (by province). All valuesare averages (TEMP) or totals (RAIN, RADPAR, BIOMSS) over the reporting period
| Alberta | 220 | -17 | 11.2 | 0 | 1228 | -2 | 933 | -12 |
| Manitoba | 236 | -22 | 12.4 | 0.2 | 1269 | 3 | 965 | -17 |
| Saskatchewan | 201 | -24 | 11.8 | 0.1 | 1253 | 1 | 850 | -19 |
| Andhra Pradesh | 509 | 16 | 30.9 | -0.6 | 1153 | -3 | 1263 | 6 |
| Assam | 1690 | 5 | 28.6 | 0 | 973 | 6 | 2347 | -6 |
| Bihar | 697 | 2 | 30.7 | -1.4 | 1157 | -5 | 1376 | -3 |
| Chhattisgarh | 825 | 20 | 30.3 | -0.7 | 1143 | -2 | 1630 | 17 |
| Daman and Diu | 975 | 28 | 29.5 | -0.5 | 1209 | -2 | 950 | -1 |
| Delhi | 510 | 58 | 32.7 | -0.3 | 1214 | -10 | 1140 | 18 |
| Gujarat | 475 | -3 | 31.8 | 0.1 | 1267 | -1 | 760 | -6 |
| Goa | 1015 | -23 | 26.3 | -0.5 | 999 | -2 | 1790 | 9 |
| Himachal Pradesh | 632 | 6 | 17 | 0.7 | 1285 | -8 | 1326 | 6 |
| Haryana | 435 | 34 | 31.6 | -0.5 | 1211 | -11 | 1150 | 19 |
| Jharkhand | 790 | 16 | 29.7 | -1.1 | 1140 | -6 | 1781 | 20 |
| Kerala | 1330 | 18 | 25.8 | -0.9 | 904 | -4 | 2350 | 13 |
| Karnataka | 723 | 11 | 26.6 | -0.8 | 1063 | -4 | 1512 | 12 |
| Meghalaya | 2351 | 0 | 24.6 | -0.3 | 936 | -1 | 2463 | 2 |
| Maharashtra | 776 | 13 | 30.1 | -0.1 | 1151 | -2 | 1323 | 11 |
| Manipur | 1019 | 0 | 22.8 | -0.2 | 973 | -3 | 2005 | -4 |
| Madhya Pradesh | 809 | 36 | 31.8 | -0.1 | 1204 | -2 | 1286 | 16 |
| Mizoram | 1838 | 30 | 23.3 | -1.2 | 990 | -5 | 2266 | 1 |
| Nagaland | 1404 | 10 | 22.4 | 0.3 | 991 | 1 | 2185 | -2 |
| Orissa | 928 | 23 | 29.7 | -0.8 | 1103 | -4 | 1922 | 19 |
| Puducherry | 121 | -48 | 31 | -0.3 | 1249 | -1 | 537 | -17 |
| Punjab | 378 | 16 | 30.6 | -0.3 | 1219 | -11 | 1120 | 20 |
| Rajasthan | 498 | 60 | 33.1 | -0.3 | 1242 | -9 | 921 | 20 |
| Sikkim | 985 | -16 | 12.5 | -1.7 | 1055 | -14 | 1242 | -10 |
| Tamil Nadu | 388 | 14 | 29.5 | -0.6 | 1184 | -3 | 1170 | 7 |
| Tripura | 2270 | 29 | 27.1 | -1.3 | 932 | -4 | 2595 | 8 |
| Uttarakhand | 763 | 4 | 20.4 | 0.2 | 1239 | -5 | 1381 | 5 |
| Uttar Pradesh | 696 | 33 | 32.1 | -0.3 | 1217 | -6 | 1214 | 8 |
| West Bengal | 1279 | 21 | 29.7 | -1.1 | 1044 | -7 | 2249 | 19 |
| Akmolin skaya | 182 | 10 | 13 | -2.2 | 1153 | -6 | 820 | 10 |
| Karagandinskaya | 200 | 16 | 13 | -2 | 1226 | -2 | 902 | 15 |
| Kustanayskaya | 149 | -5 | 14 | -2.1 | 1180 | -3 | 670 | -5 |
| Pavlodarskaya | 212 | 30 | 13.5 | -2.3 | 1121 | -8 | 952 | 31 |
| Severo kazachstanskaya | 231 | 13 | 12.5 | -2.3 | 1082 | -8 | 979 | 10 |
| Vostochno kazachstanskaya | 242 | 14 | 12.7 | -1.2 | 1282 | -2 | 956 | 13 |
| Zapadno kazachstanskaya | 94 | -18 | 18.1 | -0.5 | 1288 | 4 | 482 | -13 |
Table A.9. Russia, April-July2018 agroclimatic indicators and biomass (by oblast).All values are averages(TEMP) or totals (RAIN, RADPAR, BIOMSS) over the reporting period
| Bashkortostan Rep. | 230 | 2 | 13 | -1.4 | 1136 | -2 | 1029 | 6 |
| Chelyabinskaya Oblast | 211 | -5 | 12.4 | -1.9 | 1090 | -5 | 956 | 0 |
| Gorodovikovsk | 306 | 5 | 21 | 1.1 | 1352 | 10 | 1063 | -7 |
| Krasnodarskiy Kray | 188 | -31 | 15.4 | 0.2 | 1196 | 0 | 844 | -23 |
| Kurganskaya Oblast | 223 | 2 | 12.2 | -2.2 | 1079 | -6 | 1010 | 8 |
| Kirovskaya Oblast | 298 | 15 | 12.3 | -1 | 1075 | -1 | 1188 | 9 |
| Kurskaya Oblast | 227 | -1 | 16.5 | 0.2 | 1202 | 5 | 959 | -4 |
| Lipetskaya Oblast | 209 | -5 | 16 | 0.2 | 1201 | 5 | 929 | -4 |
| Mordoviya Rep. | 201 | -15 | 14.8 | -0.3 | 1169 | 3 | 909 | -11 |
| Novosibirskaya Oblast | 295 | 37 | 11.3 | -2 | 1069 | -8 | 1220 | 31 |
| Nizhegorodskaya O. | 223 | -11 | 14.3 | -0.2 | 1132 | 3 | 962 | -9 |
| Orenburgskaya Oblast | 136 | -16 | 15.2 | -1 | 1231 | 2 | 656 | -10 |
| Omskaya Oblast | 239 | 8 | 11.4 | -2.1 | 1063 | -7 | 1029 | 7 |
| Permskaya Oblast | 297 | 9 | 11.6 | -1.2 | 1052 | -4 | 1251 | 10 |
| Penzenskaya Oblast | 193 | -13 | 15.1 | -0.4 | 1174 | 2 | 867 | -11 |
| Rostovskaya Oblast | 181 | -12 | 19.5 | 0.6 | 1323 | 9 | 756 | -15 |
| Ryazanskaya Oblast | 195 | -19 | 15.4 | 0.2 | 1173 | 5 | 882 | -15 |
| Stavropolskiy Kray | 200 | -23 | 20.5 | 1 | 1321 | 8 | 847 | -20 |
| Sverdlovskaya Oblast | 262 | 0 | 11.5 | -1.7 | 1049 | -5 | 1122 | 3 |
| Samarskaya Oblast | 144 | -25 | 15.1 | -0.8 | 1217 | 3 | 687 | -19 |
| Saratovskaya Oblast | 156 | -7 | 16.8 | -0.4 | 1237 | 4 | 683 | -11 |
| Tambovskaya Oblast | 204 | -6 | 15.8 | 0 | 1191 | 4 | 922 | -4 |
| Tyumenskaya Oblast | 218 | -8 | 11.5 | -2 | 1076 | -5 | 971 | -4 |
| Tatarstan Rep. | 215 | 0 | 13.8 | -1.2 | 1155 | 0 | 915 | -2 |
| Ulyanovskaya Oblast | 180 | -14 | 14.9 | -0.6 | 1190 | 3 | 793 | -14 |
| Udmurtiya Rep. | 284 | 16 | 12.4 | -1.3 | 1079 | -3 | 1172 | 12 |
| Volgogradskaya O. | 174 | 8 | 18.6 | 0 | 1269 | 5 | 679 | -8 |
| Voronezhskaya Oblast | 217 | 9 | 17.1 | 0.4 | 1211 | 4 | 897 | 1 |
Table A.10. UnitedStates, April-July2018 agroclimatic indicators and biomass (by state). All values are averages(TEMP) or totals (RAIN, RADPAR, BIOMSS) over the reporting period
| Arkansas | 440 | -14 | 23 | -0.2 | 1308 | 0 | 1523 | 1 |
| California | 79 | -7 | 17 | 0.3 | 1569 | -2 | 268 | -10 |
| Idaho | 188 | 18 | 12.5 | 0.2 | 1404 | -5 | 752 | 11 |
| Indiana | 410 | -18 | 19.1 | -0.3 | 1247 | -2 | 1374 | -9 |
| Illinois | 456 | -7 | 19.3 | -0.5 | 1277 | -2 | 1401 | -5 |
| Iowa | 551 | 5 | 17.6 | -0.6 | 1276 | -2 | 1499 | -2 |
| Kansas | 524 | 15 | 20.7 | -0.2 | 1365 | -1 | 1497 | 11 |
| Michigan | 236 | -33 | 14.4 | -0.3 | 1267 | 0 | 896 | -28 |
| Minnesota | 519 | 33 | 14.7 | -0.6 | 1273 | 2 | 1475 | 13 |
| Missouri | 443 | -20 | 20.9 | -0.1 | 1303 | -1 | 1428 | -9 |
| Montana | 275 | 22 | 12.9 | -0.4 | 1323 | -5 | 1095 | 18 |
| Nebraska | 607 | 47 | 17.6 | -0.5 | 1316 | -4 | 1667 | 25 |
| North Dakota | 450 | 53 | 14.5 | 0 | 1323 | 2 | 1447 | 31 |
| Ohio | 407 | -10 | 18.2 | -0.3 | 1210 | -3 | 1451 | -2 |
| Oklahoma | 486 | -2 | 22.8 | -0.4 | 1373 | 0 | 1475 | 7 |
| Oregon | 120 | -18 | 14.2 | 0.6 | 1375 | -2 | 552 | -7 |
| South Dakota | 516 | 49 | 16.2 | -0.4 | 1309 | -3 | 1588 | 31 |
| Texas | 268 | -22 | 25.3 | 0.1 | 1397 | 1 | 914 | -12 |
| Washington | 111 | -23 | 14.4 | 0.4 | 1313 | -3 | 512 | -11 |
| Wisconsin | 457 | 3 | 14.8 | -0.6 | 1260 | 1 | 1286 | -9 |
Table A.11. China, April-July2018 agroclimatic indicators and biomass (by province). All values are averages(TEMP) or totals (RAIN, RADPAR, BIOMSS) over the reporting period
| Anhui | 730 | 1 | 23.8 | 0.2 | 1031 | -11 | 1725 | 2 |
| Chongqing | 698 | 4 | 21.6 | 0.3 | 953 | -5 | 1856 | 3 |
| Fujian | 993 | 3 | 23.4 | 0.3 | 1037 | 0 | 1972 | -2 |
| Gansu | 928 | -14 | 25.4 | -0.2 | 1021 | 2 | 1924 | -8 |
| Guangdong | 319 | 21 | 15.9 | 0 | 1125 | -11 | 1023 | 12 |
| Guangxi | 904 | -10 | 24.9 | -0.5 | 971 | -1 | 2107 | 3 |
| Guizhou | 638 | -9 | 21.5 | 0.3 | 964 | 0 | 1689 | -3 |
| Hebei | 387 | 19 | 20.4 | 0.5 | 1106 | -13 | 1224 | 11 |
| Heilongjiang | 464 | 7 | 23.3 | 0.1 | 1026 | -16 | 1414 | 9 |
| Henan | 348 | 9 | 15.9 | 0.3 | 1098 | -6 | 1205 | 7 |
| Hubei | 656 | -4 | 22.8 | 0.2 | 994 | -10 | 1710 | -2 |
| Hunan | 771 | -6 | 23.7 | 0.1 | 984 | -4 | 1953 | 2 |
| Jiangsu | 310 | -17 | 17.4 | 0.7 | 1101 | -7 | 1163 | -4 |
| Jiangxi | 524 | -6 | 23.1 | 0.2 | 1034 | -12 | 1425 | -2 |
| Jilin | 1032 | 2 | 24.7 | 0.2 | 1026 | -3 | 2149 | 4 |
| Liaoning | 295 | -26 | 18.8 | 0.5 | 1092 | -10 | 1113 | -12 |
| Inner Mongolia | 328 | 23 | 16.5 | 0.8 | 1179 | -7 | 1118 | 15 |
| Ningxia | 212 | 36 | 17.9 | 0.2 | 1182 | -13 | 767 | 19 |
| Shaanxi | 756 | 32 | 19.3 | 0 | 999 | -4 | 1673 | 9 |
| Shandong | 429 | 9 | 22.4 | 0.3 | 1090 | -14 | 1240 | 6 |
| Shanxi | 379 | 6 | 19.4 | -0.1 | 1045 | -14 | 1218 | 4 |
| Sichuan | 324 | 11 | 18.4 | 0.3 | 1110 | -15 | 1134 | 7 |
| Yunnan | 563 | -2 | 19.3 | -0.7 | 1045 | -3 | 1569 | 1 |
| Zhejiang | 976 | 18 | 23.1 | 0.3 | 1020 | -5 | 2050 | 8 |