English
中文
Bulletin
wall bulletinMenu
Executive summary
Global agroclimatic patterns
Crop and environmental conditions in major production zones
Main producing and exporting countries
- Overview
- Country analysis
- Argentina
- Australia
- Bangladesh
- Brazil
- Canada
- Germany
- Egypt
- Ethiopia
- France
- United Kingdom
- Indonesia
- India
- Iran
- Kazakhstan
- Cambodia
- Mexico
- Myanmar
- Nigeria
- Pakistan
- Philippines
- Poland
- Romania
- Russia
- Thailand
- Turkey
- Ukraine
- United States
- Uzbekistan
- Vietnam
- South Africa
- Afghanistan
- Belarus
- Mongolia
- Sri Lanka
- Zambia
- Mozambique
- Kenya
- Angola
- Hungary
- Italy
- Morocco
- UK
China
Focus and perspectives
Annex A. Agroclimatic indicators and BIOMSS 1Annex
Authors: 超级管理员 | Edit: Miao
Annex A. Agroclimatic indicators and BIOMSS
Table A.1. October 2018 - January 2019 agroclimatic indicators and biomass by global Monitoring and Reporting Unit
| code | name | 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 (%) |
| C01 | Equatorial central Africa | 522 | -1 | 25.5 | 0 | 1224 | 4 | 1503 | -1 |
| C02 | East African highlands | 151 | -13 | 20.2 | 0.5 | 1328 | 1 | 581 | -4 |
| C03 | Gulf of Guinea | 285 | 10 | 26.9 | -0.3 | 1245 | 2 | 731 | 5 |
| C04 | Horn of Africa | 268 | -13 | 24.4 | -0.6 | 1284 | 0 | 855 | -8 |
| C05 | Madagascar (main) | 756 | 1 | 24.5 | -0.4 | 1358 | 3 | 1649 | 3 |
| C06 | Southwest Madagascar | 365 | -6 | 24.7 | -0.9 | 1415 | 2 | 1082 | -3 |
| C07 | North Africa-Mediterranean | 158 | 6 | 12.7 | -0.7 | 715 | 1 | 535 | 6 |
| C08 | Sahel | 59 | 8 | 27.5 | -0.3 | 1245 | 0 | 192 | 8 |
| C09 | Southern Africa | 403 | -11 | 24.9 | -0.4 | 1442 | 5 | 1091 | -14 |
| C10 | Western Cape (South Africa) | 44 | -58 | 19 | 0.3 | 1592 | 5 | 203 | -52 |
| C11 | British Columbia to Colorado | 329 | -1 | -3 | 0.6 | 434 | 0 | 516 | 2 |
| C12 | Northern Great Plains | 251 | 25 | -0.1 | -0.4 | 453 | -6 | 614 | 0 |
| C13 | Corn Belt | 458 | 36 | 1.1 | -1.1 | 394 | -7 | 743 | -8 |
| C14 | Cotton Belt to Mexican Nordeste | 527 | 54 | 11.4 | -0.7 | 611 | -8 | 1203 | 26 |
| C15 | Sub-boreal America | 207 | -6 | -8 | -0.2 | 244 | 2 | 352 | -15 |
| C16 | West Coast (North America) | 287 | 4 | 7.5 | 0.5 | 542 | 2 | 770 | 15 |
| C17 | Sierra Madre | 169 | 43 | 14.8 | -0.4 | 1000 | -4 | 609 | 46 |
| C18 | SW U.S. and N. Mexican highlands | 152 | 35 | 7.9 | -0.4 | 751 | -4 | 549 | 32 |
| C19 | Northern South and Central America | 362 | -18 | 25.6 | -0.3 | 1070 | 4 | 888 | -15 |
| C20 | Caribbean | 204 | -36 | 24.6 | -0.4 | 1050 | 6 | 654 | -25 |
| C21 | Central-northern Andes | 593 | -3 | 16.7 | 0 | 1139 | -2 | 1259 | -1 |
| C22 | Nordeste (Brazil) | 311 | 13 | 28.3 | 0.2 | 1356 | 1 | 880 | 15 |
| C23 | Central eastern Brazil | 684 | -7 | 26.2 | -0.5 | 1318 | 6 | 1782 | -3 |
| C24 | Amazon | 851 | 1 | 27.2 | -0.9 | 1152 | 2 | 1971 | 1 |
| C25 | Central-north Argentina | 456 | 5 | 24.6 | -1.7 | 1278 | -9 | 1337 | 1 |
| C26 | Pampas | 760 | 18 | 22.5 | -0.7 | 1365 | -4 | 1715 | 7 |
| C27 | Western Patagonia | 100 | 11 | 12.2 | -1.2 | 1466 | 0 | 450 | 16 |
| C28 | Semi-arid Southern Cone | 153 | 22 | 17.6 | -1.5 | 1609 | -3 | 521 | 13 |
| C29 | Caucasus | 399 | 23 | 4.7 | 1 | 520 | -7 | 896 | 14 |
| C30 | Pamir area | 235 | 6 | 2.3 | -0.2 | 691 | -5 | 551 | 9 |
| C31 | Western Asia | 192 | 26 | 7.2 | 0.2 | 649 | -4 | 551 | 19 |
| C32 | Gansu-Xinjiang (China) | 150 | 25 | -4.8 | -0.9 | 598 | 0 | 355 | 4 |
| C33 | Hainan (China) | 170 | -55 | 22.2 | 0.5 | 805 | 7 | 484 | -21 |
| C34 | Huanghuaihai (China) | 109 | 10 | 6.2 | 0.1 | 659 | 1 | 409 | 3 |
| C35 | Inner Mongolia (China) | 47 | -42 | -5.2 | 0.7 | 602 | 3 | 220 | -31 |
| C36 | Loess region (China) | 87 | -18 | 1.2 | -0.3 | 719 | 2 | 337 | -18 |
| C37 | Lower Yangtze (China) | 222 | 1 | 11.1 | -0.4 | 555 | -15 | 785 | 11 |
| C38 | Northeast China | 69 | -34 | -5.7 | 2.4 | 504 | 4 | 309 | -13 |
| C39 | Qinghai-Tibet (China) | 100 | -36 | 0.7 | -0.7 | 895 | 1 | 307 | -22 |
| C40 | Southern China | 193 | 21 | 16.3 | -0.2 | 681 | -8 | 697 | 36 |
| C41 | Southwest China | 129 | -18 | 8.9 | -0.5 | 549 | -7 | 494 | -7 |
| C42 | Taiwan (China) | 154 | -7 | 18.9 | 0.3 | 845 | 5 | 640 | 19 |
| C43 | East Asia | 133 | -11 | -0.3 | 0.9 | 512 | 3 | 470 | -3 |
| C44 | Southern Himalayas | 124 | -12 | 17.9 | 0 | 935 | 1 | 396 | 1 |
| C45 | Southern Asia | 165 | -29 | 24.1 | 0.1 | 1117 | 2 | 424 | -23 |
| C46 | Southern Japan and the southern fringe of the Korea peninsula | 173 | -47 | 9.5 | 0.3 | 603 | 5 | 687 | -33 |
| C47 | Southern Mongolia | 175 | 83 | -10.2 | -0.1 | 497 | -1 | 388 | 22 |
| C48 | Punjab to Gujarat | 33 | -4 | 21 | -0.3 | 1013 | 1 | 134 | 11 |
| C49 | Maritime Southeast Asia | 1081 | -5 | 25.6 | -0.3 | 1106 | 5 | 2118 | -2 |
| C50 | Mainland Southeast Asia | 379 | -2 | 25.6 | 0.3 | 1070 | 4 | 928 | 15 |
| C51 | Eastern Siberia | 197 | -8 | -9.7 | 1.1 | 275 | 1 | 356 | 12 |
| C52 | Eastern Central Asia | 82 | -2 | -13.9 | 2 | 372 | 0 | 245 | 18 |
| C53 | Northern Australia | 657 | 3 | 27.2 | -0.3 | 1372 | 0 | 1353 | -6 |
| C54 | Queensland to Victoria | 202 | -14 | 21.9 | 0.9 | 1486 | 1 | 777 | -6 |
| C55 | Nullarbor to Darling | 76 | -23 | 19.1 | -0.7 | 1509 | 0 | 353 | -16 |
| C56 | New Zealand | 207 | 36 | 14.3 | 0.5 | 1301 | 4 | 723 | 12 |
| C57 | Boreal Eurasia | 321 | -15 | -4 | -0.6 | 130 | 5 | 514 | 3 |
| C58 | Ukraine to Ural mountains | 245 | -11 | -1.4 | -0.5 | 201 | 9 | 633 | -2 |
| C59 | Mediterranean Europe and Turkey | 315 | 19 | 8.8 | -0.4 | 526 | -1 | 923 | 12 |
| C60 | W. Europe (non Mediterranean) | 306 | 0 | 5.6 | -0.3 | 304 | 3 | 955 | 7 |
| C61 | Boreal America | 439 | 12 | -5.9 | 2.2 | 130 | -4 | 430 | 17 |
| C62 | Ural to Altai mountains | 189 | -1 | -8.2 | -0.2 | 273 | 3 | 397 | -3 |
| C63 | Australian desert | 126 | 9 | 21.6 | -0.4 | 1547 | -2 | 558 | 9 |
| C64 | Sahara to Afghan deserts | 109 | 69 | 17.9 | 0 | 962 | -2 | 318 | 56 |
| C65 | Sub-arctic America | 92 | -16 | -18.1 | 0.1 | 39 | 10 | 169 | 18 |
Table A.2. October 2018 - January 2019 agroclimatic indicators and biomass by country
| code | name | 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 | 638 | 29 | 21.6 | -1.3 | 1355 | -8 | 1487 | 8 |
| AUS | Australia | 233 | -7 | 22.0 | 0.6 | 1478 | 1 | 724 | -7 |
| BGD | Bangladesh | 153 | -38 | 22.4 | -0.2 | 994 | 1 | 468 | -18 |
| BRA | Brazil | 721 | -1 | 26.2 | -0.5 | 1283 | 4 | 1753 | 1 |
| KHM | Cambodia | 344 | -20 | 27.6 | 0.2 | 1133 | 6 | 942 | -2 |
| CAN | Canada | 283 | 6 | -5.6 | -0.2 | 279 | -1 | 412 | -11 |
| CHN | China | 145 | -7 | 6.8 | 0.0 | 601 | -6 | 459 | -1 |
| EGY | Egypt | 45 | -3 | 17.6 | -0.5 | 775 | 0 | 185 | 23 |
| ETH | Ethiopia | 141 | -5 | 20.9 | 0.9 | 1348 | 2 | 548 | 3 |
| FRA | France | 267 | 1 | 7.4 | -1.6 | 344 | 3 | 934 | 5 |
| DEU | Germany | 288 | -6 | 5.4 | 0.7 | 245 | 6 | 1009 | 4 |
| IND | India | 97 | -35 | 21.9 | 0.1 | 1063 | 2 | 276 | -24 |
| IDN | Indonesia | 1106 | -1 | 25.7 | -0.4 | 1130 | 4 | 2170 | -1 |
| IRN | Iran | 316 | 38 | 8.7 | 1.0 | 722 | -7 | 762 | 26 |
| KAZ | Kazakhstan | 168 | 2 | -6.5 | -0.4 | 358 | 1 | 443 | -3 |
| MEX | Mexico | 226 | 23 | 18.7 | -0.5 | 967 | -3 | 648 | 36 |
| MMR | Myanmar | 278 | 22 | 22.5 | -0.1 | 1006 | -1 | 782 | 24 |
| NGA | Nigeria | 229 | 16 | 26.9 | -0.3 | 1263 | 1 | 502 | 13 |
| PAK | Pakistan | 92 | 35 | 14.3 | -0.5 | 876 | -2 | 231 | 27 |
| PHL | Philippines | 751 | -25 | 25.5 | -0.2 | 1068 | 7 | 1442 | -18 |
| POL | Poland | 271 | -1 | 3.7 | 0.6 | 224 | 8 | 921 | 6 |
| ROU | Romania | 305 | 35 | 3.4 | 0.2 | 382 | 1 | 893 | 18 |
| RUS | Russia | 217 | -10 | -5.3 | 0.0 | 228 | 5 | 471 | 0 |
| ZAF | South Africa | 321 | -15 | 21.1 | 0.1 | 1567 | 8 | 942 | -19 |
| THA | Thailand | 395 | 10 | 25.9 | 0.5 | 1099 | 4 | 890 | 20 |
| TUR | Turkey | 421 | 26 | 6.2 | 0.9 | 533 | -8 | 1010 | 17 |
| GBR | United Kingdom | 417 | -13 | 6.9 | -1.4 | 173 | 3 | 1113 | 1 |
| UKR | Ukraine | 257 | 19 | 1.6 | -0.5 | 288 | 7 | 801 | 8 |
| USA | United States | 417 | 40 | 5.1 | -0.5 | 518 | -7 | 816 | 10 |
| UZB | Uzbekistan | 197 | -12 | 5.0 | 0.5 | 578 | -5 | 607 | 1 |
| VNM | Vietnam | 412 | -8 | 22.5 | 0.5 | 856 | 4 | 1076 | 23 |
| AFG | Afghanistan | 150 | -6 | 4.6 | -0.7 | 765 | -3 | 460 | 1 |
| AGO | Angola | 423 | -21 | 26.0 | 1.4 | 1326 | 9 | 1269 | -16 |
| BLR | Belarus | 260 | -8 | 0.4 | -0.3 | 182 | 13 | 717 | -3 |
| HUN | Hungary | 212 | 22 | 5.3 | 0.7 | 356 | 4 | 814 | 16 |
| ITA | Italy | 333 | 22 | 9.1 | 0.2 | 456 | 1 | 948 | 12 |
| KEN | Kenya | 238 | -21 | 22.3 | -0.5 | 1300 | 1 | 810 | -13 |
| LKA | Sri_Lanka | 917 | 2 | 25.8 | -0.6 | 1095 | 3 | 1790 | 2 |
| MAR | Morocco | 151 | -17 | 12.4 | -0.5 | 774 | 2 | 505 | -12 |
| MNG | Mongolia | 68 | -15 | -13.5 | 1.6 | 461 | 1 | 239 | 11 |
| MOZ | Mozambique | 603 | 12 | 26.3 | -1.4 | 1318 | 0 | 1405 | 8 |
| ZMB | Zambia | 489 | -14 | 25.2 | -0.7 | 1340 | 2 | 1357 | -14 |
Table A.3. Argentina, October 2018 -January 2019 agroclimatic indicators and biomass (by province)
| code | name | 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_BAR | Buenos Aires | 547 | 26 | 18.7 | -1.6 | 1475 | -4 | 1482 | 10 |
| ARG_CAC | Chaco | 597 | 7 | 25.2 | -1.0 | 1210 | -11 | 1612 | 4 |
| ARG_CDB | Cordoba | 524 | 24 | 21.4 | -1.4 | 1407 | -8 | 1483 | 8 |
| ARG_CRT | Corrientes | 1230 | 48 | 24.2 | -0.8 | 1268 | -10 | 1966 | 8 |
| ARG_ERS | Entre Rios | 992 | 78 | 22.0 | -1.3 | 1346 | -9 | 1757 | 14 |
| ARG_LPP | La Pampa | 506 | 28 | 20.0 | -1.5 | 1498 | -5 | 1583 | 20 |
| ARG_MSS | Misiones | 905 | -4 | 24.1 | -0.5 | 1369 | -1 | 2127 | 5 |
| ARG_SDE | Santiago Del Estero | 490 | 21 | 24.4 | -1.6 | 1214 | -13 | 1436 | 12 |
| ARG_SLS | San Luis | 449 | 16 | 20.5 | -1.5 | 1451 | -7 | 1456 | 11 |
| ARG_SLT | Salta | 457 | -5 | 23.4 | -1.7 | 1166 | -14 | 1303 | -2 |
| ARG_STF | Santa Fe | 807 | 51 | 22.8 | -1.1 | 1296 | -11 | 1736 | 11 |
| ARG_TCM | Tucuman | 306 | -23 | 22.5 | -1.7 | 1290 | -12 | 1007 | -16 |
Table A.4. Australia, October 2018 -January 2019 agroclimatic indicators and biomass (by state)
| code | name | 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 (%) |
| AUS_NSW | New South Wales | 219 | -10 | 22.9 | 1.3 | 1514 | 0 | 812 | -6 |
| AUS_SOU | South Australia | 134 | 25 | 19.5 | 0.2 | 1452 | -1 | 637 | 24 |
| AUS_VCT | Victoria | 166 | 12 | 18.7 | 0.8 | 1409 | 1 | 735 | 11 |
| AUS_WES | W. Australia | 99 | -25 | 19.8 | -0.6 | 1512 | 0 | 379 | -16 |
Table A.5. Brazil, October 2018 - January 2019 agroclimatic indicators and biomass (by state)
| code | name | 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 (%) |
| BRA_CEA | Ceara | 303 | 67 | 28.8 | 0.1 | 1380 | 0 | 915 | 79 |
| BRA_GOS | Goias | 726 | -9 | 25.7 | -0.5 | 1353 | 8 | 2045 | -1 |
| BRA_MGD | Mato Grosso Do Sul | 611 | -16 | 27.2 | -0.3 | 1438 | 10 | 1759 | -10 |
| BRA_MGO | Mato Grosso | 927 | -5 | 26.5 | -1.2 | 1219 | 7 | 2279 | 0 |
| BRA_MGS | Minas Gerais | 696 | -13 | 24.9 | 0.1 | 1295 | 4 | 1744 | -6 |
| BRA_PAA | Parana | 667 | -14 | 23.9 | 0.2 | 1388 | 6 | 1834 | -5 |
| BRA_RGD | Rio Grande Do Sul | 880 | 13 | 23.1 | 0.0 | 1362 | -2 | 1914 | 10 |
| BRA_SCA | Santa Catarina | 860 | 2 | 21.7 | 0.4 | 1279 | 1 | 1921 | -1 |
| BRA_SPL | Sao Paulo | 644 | -14 | 25.1 | 0.3 | 1334 | 7 | 1887 | -2 |
Table A.6. Canada, October 2018 - January 2019 agroclimatic indicators and biomass (by province)
| code | name | 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 (%) |
| CAN_ABT | Alberta | 136 | -13 | -5.1 | 1.5 | 275 | 2 | 425 | -2 |
| CAN_MTB | Manitoba | 174 | -14 | -8.4 | -1.2 | 277 | -2 | 351 | -23 |
| CAN_SKC | Saskatchewan | 132 | -20 | -7.2 | 0.1 | 285 | 0 | 377 | -13 |
Table A.7. India, October 2018 - January 2019 agroclimatic indicators and biomass (by state)
| code | name | 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 (%) |
| IND_ADP | Andhra Pradesh | 82 | -63 | 25.3 | 0.0 | 1128 | 1 | 306 | -43 |
| IND_ASM | Assam | 93 | -54 | 22.0 | 0.2 | 909 | 3 | 384 | -31 |
| IND_BIH | Bihar | 40 | -46 | 20.8 | -0.8 | 992 | 2 | 180 | -28 |
| IND_CTG | Chhattisgarh | 42 | -59 | 22.2 | 0.1 | 1092 | 1 | 187 | -44 |
| IND_DAD | Daman and Diu | 46 | -29 | 25.0 | -0.7 | 1197 | 4 | 164 | -21 |
| IND_DLH | Delhi | 44 | 3 | 18.9 | -0.3 | 921 | -1 | 215 | 36 |
| IND_GJR | Gujarat | 34 | -23 | 24.8 | 0.3 | 1135 | 3 | 150 | -1 |
| IND_GOA | Goa | 208 | 2 | 25.2 | 0.4 | 1218 | 1 | 560 | 4 |
| IND_HCP | Himachal Pradesh | 153 | 1 | 3.8 | 0.5 | 864 | -4 | 358 | 2 |
| IND_HYN | Haryana | 66 | 23 | 17.9 | -0.6 | 911 | 0 | 250 | 29 |
| IND_JKH | Jharkhand | 41 | -56 | 20.4 | -0.4 | 1023 | 0 | 176 | -46 |
| IND_KRL | Kerala | 510 | -4 | 25.1 | -0.4 | 1136 | 0 | 1002 | -11 |
| IND_KRT | Karnataka | 160 | -26 | 24.2 | -0.1 | 1174 | 3 | 445 | -20 |
| IND_MHL | Meghalaya | 67 | -74 | 18.8 | 0.7 | 923 | 4 | 311 | -43 |
| IND_MHT | Maharashtra | 59 | -44 | 24.4 | 0.6 | 1175 | 3 | 183 | -40 |
| IND_MIP | Manipur | 110 | -45 | 16.9 | 0.7 | 972 | 8 | 395 | -34 |
| IND_MYP | Madhya Pradesh | 25 | -51 | 21.7 | 0.3 | 1087 | 4 | 110 | -45 |
| IND_MZR | Mizoram | 241 | -16 | 18.1 | -0.2 | 1005 | 3 | 663 | -4 |
| IND_NGL | Nagaland | 61 | -68 | 16.2 | 0.5 | 865 | 4 | 296 | -51 |
| IND_ORS | Orissa | 135 | -21 | 23.1 | 0.1 | 1077 | 1 | 429 | -9 |
| IND_PDC | Puducherry | 852 | -1 | 26.5 | -0.5 | 1198 | 8 | 1459 | 10 |
| IND_PJB | Punjab | 104 | 53 | 17.4 | 0.3 | 851 | -1 | 352 | 32 |
| IND_RJT | Rajasthan | 12 | -39 | 20.7 | -0.4 | 1024 | 2 | 56 | -24 |
| IND_SKM | Sikkim | 90 | -53 | 4.7 | -0.4 | 1092 | 4 | 286 | -30 |
| IND_TND | Tamil Nadu | 432 | -19 | 26.1 | -0.4 | 1131 | 6 | 1062 | -5 |
| IND_TPR | Tripura | 201 | -38 | 21.4 | -0.4 | 967 | 0 | 640 | -3 |
| IND_UTK | Uttarakhand | 165 | 3 | 9.4 | 1.0 | 949 | 0 | 391 | 5 |
| IND_UTP | Uttar Pradesh | 53 | -26 | 20.0 | -0.1 | 984 | 2 | 200 | -17 |
| IND_WBG | West Bengal | 79 | -55 | 22.7 | 0.1 | 1017 | 1 | 291 | -34 |
Table A.8. Kazakhstan, October 2018 -January 2019 agroclimatic indicators and biomass (by province)
| code | name | 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 (%) |
| KAZ_ALS | Akmolinskaya | 157 | 11 | -8.6 | -0.5 | 307 | 1 | 385 | -7 |
| KAZ_KGS | Karagandinskaya | 143 | 14 | -8.6 | -0.8 | 376 | 0 | 372 | -9 |
| KAZ_KTS | Kustanayskaya | 123 | -17 | -7.6 | -0.5 | 285 | 5 | 429 | -3 |
| KAZ_PLS | Pavlodarskaya | 124 | 4 | -8.4 | -0.3 | 293 | 4 | 400 | -4 |
| KAZ_SKS | Severo kazachstanskaya | 152 | -3 | -8.2 | -0.1 | 244 | 5 | 395 | -4 |
| KAZ_VKS | Vostochno kazachstanskaya | 194 | -1 | -9.9 | -0.7 | 403 | 1 | 357 | -8 |
| KAZ_ZKS | Zapadno kazachstanskaya | 206 | 12 | -3.6 | -0.8 | 310 | 7 | 563 | -5 |
Table A.9. Russia, agroclimatic indicators and biomass (by oblast, kray and republic)
| code | name | 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 (%) |
| RUS_BKR | Bashkortostan Rep. | 201 | -20 | -6.3 | -0.3 | 195 | 2 | 429 | -5 |
| RUS_CBO | Chelyabinskaya Oblast | 136 | -13 | -7.2 | -0.3 | 223 | 4 | 417 | -2 |
| RUS_GRD | Gorodovikovsk | 393 | 44 | 3.6 | 0.0 | 320 | -3 | 927 | 8 |
| RUS_KDK | Krasnodarskiy Kray | 256 | 5 | -3.2 | 0.2 | 291 | 2 | 543 | 9 |
| RUS_KGO | Kurganskaya Oblast | 152 | -12 | -7.6 | 0.1 | 193 | 5 | 412 | -1 |
| RUS_KRO | Kirovskaya Oblast | 268 | -14 | -5.0 | 0.1 | 105 | -7 | 457 | -4 |
| RUS_KSO | Kurskaya Oblast | 221 | -21 | -1.1 | -0.9 | 226 | 16 | 647 | -7 |
| RUS_LSO | Lipetskaya Oblast | 207 | -24 | -2.2 | -1.2 | 214 | 14 | 599 | -9 |
| RUS_MDR | Mordoviya Rep. | 185 | -33 | -3.7 | -1.0 | 186 | 13 | 530 | -8 |
| RUS_NBO | Novosibirskaya Oblast | 223 | 3 | -10.0 | -0.2 | 200 | 5 | 355 | -2 |
| RUS_NZO | Nizhegorodskaya O. | 212 | -29 | -3.5 | -0.5 | 141 | 5 | 528 | -7 |
| RUS_OBO | Orenburgskaya Oblast | 176 | -16 | -6.0 | -0.9 | 273 | 9 | 461 | -7 |
| RUS_OKO | Omskaya Oblast | 205 | 6 | -9.3 | 0.1 | 179 | 1 | 363 | -3 |
| RUS_PMO | Permskaya Oblast | 280 | -4 | -6.5 | 0.4 | 111 | -10 | 413 | -2 |
| RUS_PZO | Penzenskaya Oblast | 206 | -25 | -3.8 | -1.1 | 205 | 12 | 532 | -9 |
| RUS_RSO | Rostovskaya Oblast | 286 | 42 | 1.7 | -0.3 | 308 | 1 | 805 | 9 |
| RUS_RYO | Ryazanskaya Oblast | 200 | -30 | -2.9 | -1.1 | 186 | 18 | 564 | -9 |
| RUS_SLK | Stavropolskiy Kray | 264 | 21 | 4.2 | 0.3 | 357 | -1 | 900 | 16 |
| RUS_SLO | Sverdlovskaya Oblast | 195 | -6 | -7.1 | 0.6 | 137 | -3 | 407 | 1 |
| RUS_SSO | Samarskaya Oblast | 207 | -14 | -4.8 | -1.0 | 226 | 12 | 508 | -6 |
| RUS_STO | Saratovskaya Oblast | 240 | 5 | -3.3 | -1.2 | 261 | 11 | 574 | -6 |
| RUS_TBO | Tambovskaya Oblast | 204 | -27 | -2.8 | -1.2 | 211 | 9 | 572 | -10 |
| RUS_TSO | Tyumenskaya Oblast | 197 | -3 | -8.4 | 0.4 | 155 | 1 | 382 | -1 |
| RUS_TSR | Tatarstan Rep. | 206 | -23 | -4.7 | -0.6 | 170 | 10 | 489 | -7 |
| RUS_USO | Ulyanovskaya Oblast | 207 | -15 | -4.4 | -1.1 | 207 | 15 | 517 | -8 |
| RUS_UTR | Udmurtiya Rep. | 253 | -13 | -5.4 | 0.1 | 121 | -5 | 450 | -4 |
| RUS_VLO | Volgogradskaya O. | 301 | 37 | -0.8 | -0.8 | 285 | 3 | 683 | -4 |
| RUS_VRO | Voronezhskaya Oblast | 229 | -12 | -1.2 | -0.7 | 259 | 12 | 649 | -6 |
Table A.10. United States, October 2018 -January 2019 agroclimatic indicators and biomass (by state)
| code | name | 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 (%) |
| USA_AKS | Arkansas | 704 | 42 | 9.2 | -0.8 | 540 | -10 | 1324 | 5 |
| USA_CLF | California | 219 | 13 | 8.7 | 0.6 | 651 | 0 | 688 | 23 |
| USA_IDH | Idaho | 290 | 10 | -1.9 | 0.0 | 466 | 2 | 597 | 2 |
| USA_IDN | Indiana | 445 | 28 | 4.0 | -0.6 | 443 | -6 | 953 | -4 |
| USA_ILN | Illinois | 414 | 26 | 3.4 | -1.0 | 466 | -4 | 915 | -5 |
| USA_IOW | Iowa | 399 | 57 | 0.2 | -1.1 | 446 | -7 | 724 | -7 |
| USA_KSS | Kansas | 277 | 71 | 4.2 | -1.1 | 556 | -11 | 748 | 30 |
| USA_MCG | Michigan | 367 | 25 | 0.1 | -1.1 | 321 | -9 | 703 | -9 |
| USA_MNS | Minnesota | 280 | 11 | -4.2 | -1.4 | 353 | -7 | 503 | -17 |
| USA_MSR | Missouri | 461 | 31 | 5.0 | -1.0 | 500 | -9 | 1017 | 3 |
| USA_MTN | Montana | 258 | 16 | -1.2 | 0.9 | 423 | -2 | 615 | 1 |
| USA_NBS | Nebraska | 216 | 20 | 1.3 | -0.6 | 533 | -6 | 717 | 6 |
| USA_NDK | North Dakota | 233 | 13 | -4.4 | -0.5 | 370 | -6 | 491 | -11 |
| USA_OHO | Ohio | 442 | 39 | 3.9 | -0.5 | 416 | -7 | 946 | -3 |
| USA_OKH | Oklahoma | 386 | 51 | 7.8 | -1.3 | 582 | -12 | 984 | 20 |
| USA_ORG | Oregon | 276 | -3 | 3.8 | 0.4 | 421 | 4 | 808 | 6 |
| USA_SDK | South Dakota | 235 | 17 | -1.1 | -0.7 | 465 | -4 | 636 | -4 |
| USA_TES | Texas | 436 | 66 | 12.1 | -1.3 | 641 | -12 | 1028 | 42 |
| USA_WHT | Washington | 346 | 4 | 3.0 | 0.8 | 353 | 8 | 840 | 11 |
| USA_WSC | Wisconsin | 350 | 22 | -1.8 | -1.1 | 364 | -7 | 612 | -12 |
Table A.11. China, October 2018 - January 2019 agroclimatic indicators and biomass (by province)
| code | name | 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 (%) |
| CHN_AHS | Anhui | 191 | -8 | 9.6 | 0.0 | 602 | -8 | 667 | -8 |
| CHN_CQS | Chongqing | 134 | -32 | 8.2 | -1.0 | 492 | -13 | 562 | -11 |
| CHN_FJS | Fujian | 248 | 24 | 13.8 | 0.3 | 561 | -13 | 915 | 50 |
| CHN_GSS | Gansu | 97 | -1 | -0.3 | -0.7 | 714 | 0 | 325 | -9 |
| CHN_GDS | Guangdong | 162 | -2 | 17.0 | 0.0 | 655 | -11 | 639 | 29 |
| CHN_GXZ | Guangxi | 159 | -15 | 15.0 | -0.8 | 536 | -21 | 614 | 11 |
| CHN_GZS | Guizhou | 124 | -27 | 9.5 | -0.6 | 389 | -21 | 491 | -11 |
| CHN_HEB | Hebei | 35 | -45 | 0.3 | 0.0 | 646 | 3 | 172 | -38 |
| CHN_HLJ | Heilongjiang | 73 | -32 | -7.2 | 3.0 | 454 | 3 | 323 | -4 |
| CHN_HEN | Henan | 87 | -31 | 7.5 | 0.0 | 665 | -2 | 391 | -25 |
| CHN_HUB | Hubei | 179 | -8 | 8.6 | -0.4 | 588 | -11 | 676 | -1 |
| CHN_HUN | Hunan | 213 | -2 | 10.0 | -1.0 | 504 | -20 | 774 | 12 |
| CHN_JSS | Jiangsu | 188 | 0 | 9.2 | 0.1 | 621 | -5 | 698 | 1 |
| CHN_JXS | Jiangxi | 262 | 6 | 11.7 | -0.5 | 534 | -18 | 833 | 12 |
| CHN_JLS | Jilin | 66 | -38 | -4.6 | 2.1 | 551 | 5 | 305 | -23 |
| CHN_LNS | Liaoning | 59 | -38 | -1.0 | 1.0 | 603 | 5 | 272 | -34 |
| CHN_NMG | Inner Mongolia | 51 | -38 | -6.9 | 1.5 | 553 | 3 | 239 | -21 |
| CHN_NXZ | Ningxia | 109 | 47 | -1.3 | -0.7 | 718 | -1 | 338 | 18 |
| CHN_SHX | Shaanxi | 96 | -36 | 2.9 | -0.5 | 704 | 2 | 417 | -22 |
| CHN_SDS | Shandong | 159 | 55 | 6.1 | 0.2 | 667 | 1 | 549 | 34 |
| CHN_SXI | Shanxi | 66 | -23 | -0.7 | -0.1 | 687 | 3 | 261 | -27 |
| CHN_SCS | Sichuan | 83 | -31 | 7.4 | -0.7 | 610 | -2 | 335 | -21 |
| CHN_YNS | Yunnan | 211 | 50 | 12.1 | -0.1 | 755 | 3 | 652 | 35 |
| CHN_ZJS | Zhejiang | 256 | 0 | 11.0 | 0.1 | 538 | -13 | 962 | 20 |