Data for 2020
Climate Readiness (ND-GAIN), 2020
2020, as ND-GAIN’s 2026 release gives it · stored as published, never rewritten
Climate Readiness (ND-GAIN), 2020 covers 192 countries. Singapore is highest, at 0.81215; Central African Republic is lowest, at 0.12205. The middle country reads 0.40951. Against 2019, 192 values changed (99 up, 93 down), the same countries are covered.
Climate Readiness (ND-GAIN) · Data for 2020
HighestSingapore
0.81215LowestCentral African Republic
0.12205Shaded by value in five groups of equal size, darkest at the better end.
01ND-GAIN’s rank
The table
Every country and every column of Climate Readiness (ND-GAIN), 2020, as published. The rank is ND-GAIN’s own, as printed. “=” marks a shared position.
Showing 25 of 192 countries · select a heading to sort
| 1 | SGPSouth-eastern Asia | 0.81215 |
| 2 | DNKNorthern Europe | 0.79493 |
| 3 | NORNorthern Europe | 0.77799 |
| 4 | FINNorthern Europe | 0.77312 |
| 5 | SWENorthern Europe | 0.74208 |
| 6 | KOREastern Asia | 0.74023 |
| 7 | ISLNorthern Europe | 0.72146 |
| 8 | MCOWestern Europe | 0.71656 |
| 9 | CHEWestern Europe | 0.71069 |
| 10 | NZLAustralia and New Zealand | 0.70866 |
| 11 | DEUWestern Europe | 0.70312 |
| =12 | JPNEastern Asia | 0.70116 |
| =12 | GBRNorthern Europe | 0.70147 |
| 14 | AUTWestern Europe | 0.69981 |
| 15 | NLDWestern Europe | 0.69727 |
| =16 | AUSAustralia and New Zealand | 0.68883 |
| =16 | LUXWestern Europe | 0.68934 |
| 18 | FRAWestern Europe | 0.65726 |
| =19 | CANNorthern America | 0.65567 |
| =19 | USANorthern America | 0.65608 |
| 21 | SMRSouthern Europe | 0.64999 |
| 22 | LIEWestern Europe | 0.64800 |
| 23 | ESTNorthern Europe | 0.63902 |
| 24 | LTUNorthern Europe | 0.61487 |
| 25 | IRLNorthern Europe | 0.61066 |
| 26 | BELWestern Europe | 0.61006 |
| 27 | SVNSouthern Europe | 0.60128 |
| 28 | AREWestern Asia | 0.59668 |
| 29 | LVANorthern Europe | 0.59345 |
| 30 | PRTSouthern Europe | 0.58899 |
| 31 | MUSEastern Africa | 0.58053 |
| 32 | GEOWestern Asia | 0.57898 |
| 33 | ISRWestern Asia | 0.56170 |
| =34 | ANDSouthern Europe | 0.56109 |
| =34 | KNACaribbean | 0.56140 |
| 36 | CZEEastern Europe | 0.55992 |
| 37 | NRUMicronesia | 0.55811 |
| 38 | POLEastern Europe | 0.55298 |
| 39 | CHNEastern Asia | 0.55132 |
| 40 | ESPSouthern Europe | 0.54542 |
| 41 | CHLSouth America | 0.54188 |
| 42 | QATWestern Asia | 0.54059 |
| =43 | BRBCaribbean | 0.54030 |
| =43 | SAUWestern Asia | 0.54023 |
| =45 | CYPWestern Asia | 0.53828 |
| =45 | GRCSouthern Europe | 0.53813 |
| 47 | ITASouthern Europe | 0.53647 |
| 48 | BRNSouth-eastern Asia | 0.53145 |
| 49 | RUSEastern Europe | 0.52438 |
| 50 | MYSSouth-eastern Asia | 0.52249 |
| 51 | GRDCaribbean | 0.52040 |
| 52 | DMACaribbean | 0.51596 |
| 53 | MLTSouthern Europe | 0.51419 |
| =54 | SVKEastern Europe | 0.51072 |
| =54 | URYSouth America | 0.51067 |
| 56 | ARMWestern Asia | 0.50829 |
| =57 | OMNWestern Asia | 0.50485 |
| =57 | VCTCaribbean | 0.50457 |
| 59 | HUNEastern Europe | 0.50354 |
| 60 | BHRWestern Asia | 0.49501 |
| 61 | PLWMicronesia | 0.49297 |
| 62 | HRVSouthern Europe | 0.49050 |
| 63 | FJIMelanesia | 0.48895 |
| =64 | BLREastern Europe | 0.48688 |
| =64 | KAZCentral Asia | 0.48737 |
| =64 | THASouth-eastern Asia | 0.48695 |
| 67 | SYCEastern Africa | 0.48567 |
| 68 | ROUEastern Europe | 0.48461 |
| 69 | TURWestern Asia | 0.47895 |
| 70 | MNESouthern Europe | 0.47650 |
| 71 | CRICentral America | 0.47018 |
| 72 | BGREastern Europe | 0.46896 |
| 73 | MKDSouthern Europe | 0.46750 |
| 74 | BTNSouthern Asia | 0.46491 |
| 75 | TUNNorthern Africa | 0.45388 |
| 76 | ATGCaribbean | 0.45250 |
| 77 | CPVWestern Africa | 0.45152 |
| 78 | KWTWestern Asia | 0.44862 |
| =79 | LCACaribbean | 0.44416 |
| =79 | SRBSouthern Europe | 0.44427 |
| 81 | WSMPolynesia | 0.44334 |
| 82 | MARNorthern Africa | 0.44190 |
| =83 | BHSCaribbean | 0.43643 |
| =83 | TONPolynesia | 0.43613 |
| =85 | AZEWestern Asia | 0.43489 |
| =85 | MNGEastern Asia | 0.43509 |
| =85 | VNMSouth-eastern Asia | 0.43530 |
| 88 | MDVSouthern Asia | 0.43193 |
| 89 | SLBMelanesia | 0.42679 |
| =90 | MDAEastern Europe | 0.41997 |
| =90 | TUVPolynesia | 0.41958 |
| 92 | BWASouthern Africa | 0.41659 |
| 93 | JORWestern Asia | 0.41518 |
| 94 | UKREastern Europe | 0.41288 |
| 95 | RWAEastern Africa | 0.41194 |
| 96 | MHLMicronesia | 0.40955 |
| 97 | ALBSouthern Europe | 0.40946 |
| 98 | LKASouthern Asia | 0.40576 |
| 99 | PERSouth America | 0.40368 |
| =100 | IDNSouth-eastern Asia | 0.40090 |
| =100 | JAMCaribbean | 0.40110 |
| 102 | PANCentral America | 0.39759 |
| 103 | TLSSouth-eastern Asia | 0.39364 |
| 104 | KIRMicronesia | 0.38251 |
| 105 | INDSouthern Asia | 0.38186 |
| 106 | ARGSouth America | 0.38045 |
| 107 | IRNSouthern Asia | 0.37761 |
| 108 | KGZCentral Asia | 0.37709 |
| 109 | NAMSouthern Africa | 0.37650 |
| 110 | COLSouth America | 0.37541 |
| 111 | UZBCentral Asia | 0.37170 |
| =112 | BIHSouthern Europe | 0.36666 |
| =112 | DOMCaribbean | 0.36652 |
| =114 | MEXCentral America | 0.36635 |
| =114 | STPMiddle Africa | 0.36625 |
| =114 | VUTMelanesia | 0.36563 |
| =117 | PRKEastern Asia | 0.36208 |
| =117 | ZAFSouthern Africa | 0.36166 |
| 119 | FSMMicronesia | 0.36076 |
| 120 | SENWestern Africa | 0.35919 |
| =121 | PRYSouth America | 0.35480 |
| =121 | TGOWestern Africa | 0.35545 |
| 123 | SLVCentral America | 0.35391 |
| 124 | GHAWestern Africa | 0.35180 |
| 125 | TTOCaribbean | 0.35139 |
| 126 | BRASouth America | 0.34957 |
| 127 | BLZCentral America | 0.34694 |
| 128 | CUBCaribbean | 0.34630 |
| 129 | GUYSouth America | 0.34548 |
| =130 | ECUSouth America | 0.34328 |
| =130 | EGYNorthern Africa | 0.34321 |
| =130 | GMBWestern Africa | 0.34295 |
| =133 | MRTWestern Africa | 0.34237 |
| =133 | PHLSouth-eastern Asia | 0.34154 |
| 135 | BENWestern Africa | 0.33920 |
| 136 | NPLSouthern Asia | 0.33822 |
| 137 | DJIEastern Africa | 0.33624 |
| 138 | SURSouth America | 0.33225 |
| 139 | DZANorthern Africa | 0.32894 |
| 140 | NERWestern Africa | 0.32264 |
| 141 | TJKCentral Asia | 0.32011 |
| 142 | LAOSouth-eastern Asia | 0.31790 |
| 143 | SWZSouthern Africa | 0.31546 |
| 144 | GTMCentral America | 0.31221 |
| 145 | PAKSouthern Asia | 0.31120 |
| 146 | GINWestern Africa | 0.30938 |
| 147 | LSOSouthern Africa | 0.30679 |
| 148 | ZMBEastern Africa | 0.30353 |
| 149 | SLEWestern Africa | 0.29887 |
| 150 | LBNWestern Asia | 0.29715 |
| 151 | TZAEastern Africa | 0.29533 |
| 152 | MMRSouth-eastern Asia | 0.29039 |
| 153 | CIVWestern Africa | 0.28940 |
| 154 | KENEastern Africa | 0.28738 |
| =155 | ETHEastern Africa | 0.28453 |
| =155 | NICCentral America | 0.28483 |
| 157 | KHMSouth-eastern Asia | 0.28433 |
| 158 | PNGMelanesia | 0.28300 |
| =159 | BOLSouth America | 0.28122 |
| =159 | IRQWestern Asia | 0.28061 |
| =159 | MLIWestern Africa | 0.28078 |
| 162 | GABMiddle Africa | 0.28048 |
| 163 | LBRWestern Africa | 0.27918 |
| 164 | COMEastern Africa | 0.27676 |
| 165 | MWIEastern Africa | 0.27528 |
| 166 | BFAWestern Africa | 0.26946 |
| 167 | UGAEastern Africa | 0.26692 |
| =168 | BGDSouthern Asia | 0.26587 |
| =168 | GNBWestern Africa | 0.26622 |
| =170 | HNDCentral America | 0.26478 |
| =170 | MDGEastern Africa | 0.26499 |
| 172 | MOZEastern Africa | 0.25999 |
| 173 | BDIEastern Africa | 0.25399 |
| 174 | SDNNorthern Africa | 0.25122 |
| 175 | CMRMiddle Africa | 0.24778 |
| 176 | TKMCentral Asia | 0.24567 |
| 177 | SOMEastern Africa | 0.24476 |
| 178 | YEMWestern Asia | 0.24401 |
| 179 | AGOMiddle Africa | 0.24233 |
| =180 | GNQMiddle Africa | 0.23512 |
| =180 | NGAWestern Africa | 0.23507 |
| 182 | SYRWestern Asia | 0.22987 |
| 183 | LBYNorthern Africa | 0.22688 |
| 184 | AFGSouthern Asia | 0.22650 |
| 185 | HTICaribbean | 0.21978 |
| 186 | COGMiddle Africa | 0.21016 |
| 187 | ZWEEastern Africa | 0.20592 |
| 188 | CODMiddle Africa | 0.18778 |
| 189 | ERIEastern Africa | 0.18724 |
| 190 | VENSouth America | 0.17455 |
| 191 | TCDMiddle Africa | 0.17008 |
| 192 | CAFMiddle Africa | 0.12205 |
02In 2020
At either end
The 5 countries at each end of the headline.
Lowest
- #192
Central African Republic0.12205
- #191
Chad0.17008
- #190
Venezuela0.17455
- #189
Eritrea0.18724
- #188
DR Congo0.18778
A higher value is the better result. The middle country reads 0.40951. “Shared” marks a value another country also holds.
032019 → 2020
Since 2019
What changed between 2019 and this one: who joined or left, and how far the headline moved.
- +0 / −0countries joined / left
- 192values changed, of 192 in both
- 99 · 93rose · fell
- 0unchanged
Rose most
Saudi Arabia0.50792 → 0.54023+0.03231
Kuwait0.41808 → 0.44862+0.03054
Togo0.32567 → 0.35545+0.02978
Bahrain0.47009 → 0.49501+0.02492
Pakistan0.28732 → 0.31120+0.02387
Fell most
Monaco0.78253 → 0.71656−0.06596
Belarus0.51099 → 0.48688−0.02410
France0.67351 → 0.65726−0.01625
Australia0.70124 → 0.68883−0.01241
Marshall Islands0.42182 → 0.40955−0.01227
Both years come from the same release, so a difference here is a change in the data, not a revision of it. Every country’s full history is charted on the statistic page.
04Caveats
Read before you use
What this edition’s numbers are and are not, worked out from the file itself.
One year of the 2026 release
Every year in this series comes from ND-GAIN’s 2026 release, recalculated on one method. It can differ from what was first published for 2020.
The rank is ND-GAIN’s
Printed as the publisher ranked the countries; never re-ranked here.
Nothing missing
Every one of the 192 countries has every column.
05The files
Download and cite
The table as a file, digit for digit, what this site changed, and a citation for this edition.
- .csv
For a spreadsheet or code
192 rows · 8.1 KB · UTF-8, opens in Excel
Opens with 11 lines of source notes; the table starts on row 13.
Download climate-readiness-2020-nations-inquiry.csv - ↗
The publisher’s original
ND-GAIN’s own file, on its own site.
resources-2026-14-07-13h00.zip
What this site changed: Reshaped into one row per country: regional and income-group totals are left out, only the columns listed are kept, each row gets its ISO 3166 code, and some country names are brought to one spelling. No value is recalculated, rescaled or rounded.
Licence: CC BY 3.0 Unported · what it allows, in plain words
Cite this edition
Notre Dame Global Adaptation Initiative (ND-GAIN), University of Notre Dame (2020). Climate Readiness (ND-GAIN), 2020 [data set], describing 2020. As held by Nations Inquiry, https://nationsinquiry.com/datasets/climate-readiness/2020
0630 held
Other years
‹ The year before
Climate Readiness (ND-GAIN), 2019192 countries
The year after ›
Climate Readiness (ND-GAIN), 2021192 countries
All of them
Climate Readiness (ND-GAIN): every year30 held, with the data dictionary, coverage and licence.
How it has moved, charted by country
07Questions
Climate Readiness (ND-GAIN), 2020: questions and answers
Which country has the highest climate adaptation readiness in Climate Readiness (ND-GAIN), 2020?
Singapore, at 0.81215, of the 192 countries in the file.
What year does Climate Readiness (ND-GAIN), 2020 describe?
2020.
How many countries does Climate Readiness (ND-GAIN), 2020 cover?
192.
Where can I download Climate Readiness (ND-GAIN), 2020?
On this page, as a CSV file holding every value exactly as published, or from the publisher’s own site, linked below.
Is Climate Readiness (ND-GAIN), 2020 the newest?
No. The newest held here is Climate Readiness (ND-GAIN), 2024.